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Applying ANN,ANFIS and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO_(2)

Computers, Materials & Continua 2020年第6期63卷 1175-1204页

作者： Amin Bemani a.ireza Baghban Shahaboddin Shamshirband Amir mosavi Peter Csiba Annamaria R.Varkonyi-Koczy Petroleum Engineering Department Petroleum University of TechnologyAhwazIran Chemical Engineering Department Amirkabir University of TechnologyMahshahr CampusMahshahrIran Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi MinhVietnam Faculty of Information Technology Ton Duc Thang UniversityHo Chi MinhVietnam Kalman Kando Faculty of Electrical Engineering Obuda UniversityBudapest1034Hungary Institute of Structural Mechanics Bauhaus University WeimarWeimarD-99423Germany Department of Mathematics and Informatics J.Selye UniversityKomarno94501Slovakia

In the present work,a novel machine learning computational investigation is carried out to accurately predict the solubility of different acids in supercritical carbon *** different machine learning algorithms of radial basis function,multi-layer perceptron(MLP),artificial neural networks(ANN),least squares support vector machine(LSSVM)and adaptive neuro-fuzzy inference system(ANFIS)are used to model the solubility of different acids in carbon dioxide based on the temperature,pressure,hydrogen number,carbon number,molecular weight,and the dissociation constant of *** evaluate the proposed models,different graphical and statistical analyses,along with novel sensitivity analysis,are carried *** present study proposes an efficient tool for acid solubility estimation in supercritical carbon dioxide,which can be highly beneficial for engineers and chemists to predict operational conditions in industries.

关键词： Supercritical carbon dioxide machine learning acid artificial intelligence solubility artificial neural networks(ANN) adaptive neuro-fuzzy inference system(ANFIS) least-squares support vector machine(LSSVM) multilayer perceptron(MLP)

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A Fused Machine Learning Approach for Intrusion Detection System

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Computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Two Layer Symmetric Cryptography Algorithm for Protecting Data from Attacks

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Computers, Materials & Continua 2023年第2期74卷 2625-2640页

作者： Muhammad Nadeem Ali Arshad Saman Riaz Syeda Wajiha Zahra Shahab SBand Amir mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John Von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathilticsSlovak University of Technology in BratislavaSlovakia

Many organizations have insisted on protecting the cloud server from the outside,although the risks of attacking the cloud server are mostly from the *** are many algorithms designed to protect the cloud server from attacks that have been able to protect the cloud server ***,the attackers have designed even better mechanisms to break these security *** cryptography is the best data protection algorithm that exchanges data between authentic *** this article,one symmetric cryptography algorithm will be designed to secure cloud server data,used to send and receive cloud server data securely.A double encryption algorithm will be implemented to send data in a secure ***,the XOR function will be applied to plain text,and then salt technique will be ***,a reversing mechanism will be implemented on that data to provide more data *** decrypt data,the cipher text will be reversed,salt will be removed,andXORwill be *** the end of the paper,the proposed algorithm will be compared with other algorithms,and it will conclude how much better the existing algorithm is than other algorithms.

关键词： Cryptography symmetric algorithm encryption decryption cipher text cloud security asymmetric algorithm

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Comparative study of multilayer perceptron-stochastic gradient descent and gradient boosted trees for predicting daily suspended sediment load: The case study of the Mississippi River, U.S.

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International Journal of Sediment Research 2021年第4期36卷 512-523页

作者： Sadra Shadkani Akram Abbaspour Saeed Samadianfard Sajjad Hashemi Amirhosein mosavi Shahab S.Band Department of Water Engineering Faculty of Agriculture University of Tabriz Environmental Quality Atmospheric Science and Climate Change Research Group Ton Duc Thang University Faculty of Environment and Labour Safety Ton Duc Thang University Institute of Research and Development Duy Tan University Future Technology Research Center College of Future National Yunlin University of Science and Technology

Monitoring sediment transport is essential for managing and maintaining *** of the sediment load in rivers is fundamental for the study of sediment movement,erosion,and flood *** the current study,three machine learning models-multi-layer perceptron(MLP),multi-layer perceptron-stochastic gradient descent(MLP-SGD),and gradient boosted tree(GBT)-were utilized to estimate the suspended sediment load(SSL) at the ***(SL) and Chester(CH) stations on the Mississippi River,*** evaluation criteria including the Correlation Coefficient(CC),Nash Sutcliffe Efficiency(NSE),Scatter Index(SI),and Willmott’s Index(WI) were utilized to evaluate the performance of the used models.A sensitivity analysis of the models to the input variables revealed that the current day discharge variable had the most effect on the SSL at both stations,but in the absence of current-day discharge data(Qt),a combination of input parameters including SSLt-3,SSLt-2,SSLt-1,Qt-3,Qt-2,Qt-1can be used to estimate the *** comparative outcomes indicated the high accuracy of MLP-SGD-5 model with a CC of 0.983,SI of 0.254,WI of 0.991,and NSE of 0.967 at station CH and the MLP-SGD-6 model with a CC of 0.933,SI of 0.576,WI of 0.961,and NSE of 0.867,respectively,at station *** results of MLP models were improved by SGD ***,the MLP-SGD method is recommended as the most accurate model for SSL estimation.

关键词： Suspended sediment transport Ensemble learning Multilayer perceptron Stochastic gradient descent Machine learning

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Aspect Level Songs Rating Based Upon Reviews in English

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Computers, Materials & Continua 2023年第2期74卷 2589-2605页

作者： Muhammad Aasim Qureshi Muhammad Asif Saira Anwar Umar Shaukat Atta-ur-Rahman Muhammad Adnan Khan Amir mosavi Department of Computer Science Bahria University Lahore54000Pakistan Lahore Institute of Science and Technology Lahore 54792Pakistan Department of Multidisciplinary Engineering Texas A&M UniversityCollege Station77843USA Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam 31441Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

With the advancements in internet facilities,people are more inclined towards the use of online *** service providers shelve their items for *** users post their feedbacks,reviews,ratings,*** the use of the *** enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these *** Analysis(SA)is a technique that performs such decision *** research targets the ranking and rating through sentiment analysis of these reviews,on different *** a case study,Songs are opted to design and test the decision *** aspects of songs namely music,lyrics,song,voice and video are *** the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a *** machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are *** performed the best with 74.99%*** are validated using K-Fold.

关键词： Machine learning natural language processing songs reviews:sentiment analysis songs rating aspect level sentiment analysis reviews analysis text classification music

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Evaluation of kefir as a potential probiotic on growth performance,serum biochemistry and immune responses in broiler chicks

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Animal Nutrition 2015年第4期1卷 305-309页

作者： Majid Toghyani Seyed kazem mosavi Mehrdad Modaresi Nasir Landy Department of Animal Science Khorasgan Branch Islamic Azad University Young Researchers and Elite Club Khorasgan BranchIslamic Azad University

This experiment was conducted to evaluate the effect of milk or molasses kefir as a probiotic on growth performance, carcass traits, serum biochemistry and humoral immune responses in broiler chickens. A total of 192 one-d-old as hatched broiler chicks(Ross 308) were randomly allotted to 4 treatments, each with 4 replicate pens of 12 chicks. The following treatments were applied: 1) a basal diet(C) and normal drinking water, 2) 2% milk kefir in drinking water, 3) 2% molasses kefir in drinking water, and 4) the diet C supplemented with commercial probiotic. At d 42, eight birds per treatment were killed for determination of carcass traits. Broilers at 28 days of age were bled for measuring antibody titers against Newcastle disease virus(NDV) and avian influenza virus(AIV), at 30 days of age for antibody titers against sheep red blood cell(SRBC), and at 42 days of age for biochemical analysis. Supplementing 2%milk kefir increased body weight of broilers at 28 and 42 days of age(P 0.05) influenced. Broilers supplemented with molasses kefir, had a significantly lower concentration of serum total cholesterol, low density lipoprotein cholesterol and elevated high density lipoprotein cholesterol at 42 days of age(P < 0.05). In conclusion, t

关键词： Antibiotic Milk kefir Molasses kefir Multi-strain probiotic Broilers

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A Mobile Cloud-Based eHealth Scheme

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Computers, Materials & Continua 2020年第4期63卷 31-39页

作者： Yihe Liu Aaqif Afzaal Abbasi Atefeh Aghaei Almas Abbasi Amir mosavi Shahaboddin Shamshirband Mohammed A.A.Al-qaness Data Recovery Key Laboratory of Sichuan Province College of Computer Science and AINeijiang Normal UniversityNeijiang641100China Department of Software Engineering Foundation UniversityIslamabad44000Pakistan Department of Communication Faculty of Social SciencesUniversity of TehranTehran***Iran Department of Computer Science International Islamic UniversityIslamabad46000Pakistan Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Kalman Kando Faculty of Electrical Engineering Obuda UniversityBudapest1034Hungary School of the Built Environment Oxford Brookes UniversityOxfordOX30BPUK Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam School of Computer Science Wuhan UniversityWuhan430072China

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid ***,the field of health informatics is also considered as an extremely important *** work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing *** developed system has two front ends,the first dedicated for the user to perform the photographing of the trace *** the photographing is complete,mobile computing is used to extract the *** the signal is extracted,it is uploaded into the server and further analysis is performed on the signal in the *** this is done,the second interface,intended for the use of the physician,can download and view the trace from the *** data is securely held using a password-based authentication *** system presented here is one of the first attempts at delivering the total solution,and after further upgrades,it will be possible to deploy the system in a commercial setting.

关键词： Cloud computing electrocardiograms health-care signal analysis signal processing

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Recurrent Polynomial Neural Networks for Enhancing Performance of GPS in Electric Systems

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Wireless Sensor Network 2009年第2期1卷 95-103页

作者： Mohammad Reza mosavi Associate Professor Department of Electrical Engineering Iran University of Science and Technology Narmak Iran

Global Positioning System (GPS) is a worldwide satellite system that provides navigation, positioning, and timing for both military and civilian applications. GPS based time reference provides inexpensive but highly-accurate timing and synchronization capability and meets requirements in power system fault location, monitoring, and control. In the present era of restructuring and modernization of electric power utilities, the applications of GIS/GPS technology in power industry are growing and covering several technical and man-agement activities. Because of GPS receiver’s error sources are time variant, it is necessary to remove the GPS measurement noise. This paper presents novel recurrent neural networks called the Recurrent Pi-Sigma Neural Network (RPSNN) and Recurrent Sigma-Pi Neural Network (RSPNN). The proposed NNs have been used as predictor in GPS receivers timing errors. The NNs were trained using the dynamic Back Propagation (BP) algorithm. The actual data collection was used to test the performance of the proposed NNs. The ex-perimental results obtained from a Coarse Acquisition (C/A)-code single-frequency GPS receiver strongly support the potential of the method using RPSNN to give high accurate timing. The GPS timing RMS error reduces from 200 to less than 40 nanoseconds.

关键词： Accurate Timing GPS Electric Systems Neural Networks

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Preventing Cloud Network from Spamming Attacks Using Cloudflare and KNN

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Computers, Materials & Continua 2023年第2期74卷 2641-2659页

作者： Muhammad Nadeem Ali Arshad Saman Riaz SyedaWajiha Zahra Muhammad Rashid Shahab S.Band Amir mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaSlovakia

Cloud computing is one of the most attractive and cost-saving models,which provides online services to *** computing allows the user to access data directly from any *** nowadays,cloud security is one of the biggest issues that *** types of malware are wreaking havoc on the *** on the cloud server are happening from both internal and external *** paper has developed a tool to prevent the cloud server from spamming *** an attacker attempts to use different spamming techniques on a cloud server,the attacker will be intercepted through two effective techniques:Cloudflare and K-nearest neighbors(KNN)*** will block those IP addresses that the attacker will use and prevent spamming ***,the KNN classifiers will determine which area the spammer belongs *** the end of the article,various prevention techniques for securing cloud servers will be discussed,a comparison will be made with different papers,a conclusion will be drawn based on different results.

关键词： Intrusion prevention system spamming KNN classification spam cyber security botnet

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微量元素叶面喷施对水稻(Oryza sativa L.)产量及其构成因素的影响

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植物营养与肥料学报 2021年第5期27卷 909-918页

作者： Ashkan Daneshtalab Lahijani Amirabbas mosavi Morteza Moballeghi Department of Agronomy Islamic Azad University of ChalousChalousMazandaran46615/397Iran

【目的】基于微量元素在水稻营养和代谢中的重要作用,研究叶面喷施(Fe EDTA 0.1%,Zn EDTA 0.05%,B 0.02%,Cu EDTA 0.05%,and Mn EDTA 0.05%)对水稻品种Shiroodi产量的影响,明确叶面喷施微量元素的最佳次数和时期。【方法】为了准确评估... 详细信息

【目的】基于微量元素在水稻营养和代谢中的重要作用,研究叶面喷施(Fe EDTA 0.1%,Zn EDTA 0.05%,B 0.02%,Cu EDTA 0.05%,and Mn EDTA 0.05%)对水稻品种Shiroodi产量的影响,明确叶面喷施微量元素的最佳次数和时期。【方法】为了准确评估液体肥料(Fe-EDTA 0.1%,Zn-EDTA 0.05%,B 0.02%,Cu-EDTA 0.05%,and Mn-EDTA 0.05%)对水稻品种Shiroodi产量的影响,和喷施微量元素肥料1~7次(T1~T7),第一次喷施在移栽后9天进行,之后每隔7天喷施一次。【结果】喷施微量元素显著增加了植株干重、籽粒产量、千粒重和收获指数,而且试验年份与喷施微量元素处理对籽粒含锌量、叶片叶绿素b含量和千粒重有显著交互作用。T4处理籽粒产量为4257 kg/hm^(2),而T0只有3499 kg/hm^(2),增产幅度约为20%。产量和产量构成因子的提高源于喷施微量元素肥料处理增加了每株分蘖数、穗长和穗粒数。【结论】叶面喷施有效地提高了水稻对微量元素的吸收利用,喷施4次效果最好。

关键词：水稻叶面喷施微量元素叶绿素籽粒产量

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