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Arabic Sentiment a.alysis of Users’ Opinions of Governmental Mobile Applications

Computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： mohammed Hadwan mohammed a.al-hagery mohammed al-Sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent a.alytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to a.alyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by a.alysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment a.alysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this a.alysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment a.alysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

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A Hybrid Neural Network and Box-Jenkins Models for Time Series Forecasting

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Computers, Materials & Continua 2022年第3期70卷 4829-4845页

作者： Mohammad Hadwan Basheer M.al-Ma.aleh Fuad N.al-Badani Rehan Ullah Khan mohammed a.al-hagery Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Intelligent a.alytics Group(IAG) College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Computer Sciences and Information Systems Thamar UniversityThamarYemen Faculty of Administration Science Ibb UniversityIbbYemen Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia

Time series forecasting plays a significant role in numerous applications,including but not limited to,industrial planning,water consumption,medical domains,exchange rates and consumer price *** main problem is insufficient forecasting *** present study proposes a hybrid forecastingmethods to address this *** proposed method includes three *** first model is based on the autoregressive integrated moving average(ARIMA)statistical model;the second model is a back propagation neural network(BPNN)with adaptive slope and momentum parameters;and the thirdmodel is a hybridization between ARIMA and BPNN(ARIMA/BPNN)and artificial neural networks and ARIMA(ARIMA/ANN)to gain the benefits of linear and *** forecasting models proposed in this study are used to predict the indices of the consumer price index(CPI),and predict the expected number of cancer patients in the Ibb Province in *** standard measures used to evaluate the proposed method include(i)mean square error,(ii)mean absolute error,(iii)root mean square error,and(iv)mean absolute percentage *** on the computational results,the improvement rate of forecasting the CPI dataset was 5%,71%,and 4%for ARIMA/BPNN model,ARIMA/ANN model,and BPNN model respectively;while the result for cancer patients’dataset was 7%,200%,and 19%for ARIMA/BPNNmodel,ARIMA/ANN model,and BPNNmodel ***,it is obvious that the proposed method reduced the randomness degree,and the alterations affected the time series with data *** ARIMA/ANN model outperformed each of its components when it was applied separately in terms of increasing the accuracy of forecasting and decreasing the overall errors of forecasting.

关键词： Hybrid model forecasting non-linear data time series models cancer patients neural networks box-jenkins consumer price index

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An Efficient Scheme for Interference Mitigation in 6G-IoT Wireless Networks

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Computers, Materials & Continua 2021年第12期69卷 3889-3902页

作者： Fahd N.al-Wesabi Imran Khan Nadhem Nemri mohammed a.al-hagery Huda G.Iskander Quang Ngoc Nguyen Babar Shah Ki-Il Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Communications and Computer Engineering Faculty of Science and EngineeringWaseda UniversityShinjuku-kuTokyo169-0051Japan College of Technological Innovation Zayed UniversityAbu DhabiUAE Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

The Internet of Things(IoT)is the fourth technological revolution in the global information industry after computers,the Internet,and mobile communication *** combines radio-frequency identification devices,infrared sensors,global positioning systems,and various other *** sensing equipment is connected via the Internet,thus forming a vast *** these physical devices are connected to the Internet,the user terminal can be extended and expanded to exchange information,communicate with anything,and carry out identification,positioning,tracking,monitoring,and triggering of corresponding events on each device in the *** real life,the IoT has a wide range of applications,covering many fields,such as smart homes,smart logistics,fine agriculture and animal husbandry,national defense,and *** of the most significant factors in wireless channels is interference,which degrades the system *** the existing QR decomposition-based signal detection method is an emerging topic because of its low complexity,it does not solve the problem of poor detection ***,this study proposes a maximumlikelihood-based QR decomposition *** main idea is to estimate the initial level of detection using the maximum likelihood principle,and then the other layer is detected using a reliable *** optimal candidate is selected from the feedback by deploying the candidate points in an unreliable *** results show that the proposed algorithm effectively reduces the interference and propagation error compared with the algorithms reported in the literature.

关键词： 6G networks internet of things resource allocation optimization

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali alabdulhafith Yeong Hyeon Gu mohammed a.al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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Improved Dwarf Mongoose Optimization algorithm for Feature Selection:Application in Software Fault Prediction Datasets

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Journal of Bionic Engineering 2024年第4期21卷 2000-2033页

作者： Abdelaziz I.Hammouri mohammed A.Awa.allah Malik Sh.Braik mohammed Azmi al-Betar Majdi Beseiso Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Scientific Research and Graduate Studies University of Prince Mugrin42241MedinaSaudi Arabia Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityAl-HusonIrbid21110Jordan

Feature selection(FS)plays a crucial role in pre-processing machine learning datasets,as it eliminates redundant features to improve classification accuracy and reduce computational *** paper presents an enhanced approach to FS for software fault prediction,specifically by enhancing the binary dwarf mongoose optimization(BDMO)algorithm with a crossover mechanism and a modified positioning updating *** proposed approach,termed iBDMOcr,aims to fortify exploration capability,promote population diversity,and lastly improve the wrapper-based FS process for software fault prediction *** gained superb performance compared to other well-esteemed optimization methods across 17 benchmark *** ranked first in 11 out of 17 datasets in terms of average classification ***,iBDMOcr outperformed other methods in terms of average fitness values and number of selected features across all *** findings demonstrate the effectiveness of iBDMOcr in addressing FS problems in software fault prediction,leading to more accurate and efficient models.

关键词： Dwarf mongoose optimization algorithm Optimization Feature selection Classification

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Secure android IoT mobile and collaborative machine learning for controlling the management of enterprise

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Journal of Control and Decision 2024年第1期11卷 15-25页

作者： Hamza mohammed Ridha.al-Khafaji Refed Adnan Jaleel Biomedical Engineering Department Al-Mustaqbal University CollegeHillahIraq Information and Communication Engineering Department Al-Nahrain UniversityBaghdadIraq

There is a need for increased security measures because of wide variety of android Internet of Thing(IoT)mobile devices that can communicate with each other via networks for controlling the management of *** Curve Deffie Hellman(ECDH)and Rivest Shamir Adleman(RSA)are used to secure data in android IoT phones in efficient *** mobile can store a lot of data,including sensitive *** data saved on mobile has become a critical *** android IoT,Collaborative Machine Learning describes a method for collaboratively mining data,which makes it easier to manage and lowers cost of *** increase security in IoT phones,suggested system uses ECDH,RSA,and CML algorithms,which have been considered novelty of this *** and ECDH are computed using time of decryption,encryption,and key *** show ECDH beats other alternatives like ***,all users of the network have been tested.

关键词： IoT ECDH RSA CML android encryption decryption

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Communication-less Management Strategy for Electric Vehicle Charging in Droop-controlled Islanded Microgrids

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1227-1238页

作者： Abdullah Azhar al-Obaidi mohammed Zaki El-Sharafy Hany E.Z.Farag Saifullah Shafiq ali al-Awami Independent Electricity System Operator(IESO) MississaugaCanada Department of Electrical Engineering and Computer Science York UniversityTorontoCanada University of Queensland StLucia QLD 4067Australia Department of Electrical Engineering King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

Adopting high penetration levels of electric vehicles(EVs)necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on pow-er distribution ***,most of the proposed Ev charging management techniques rely on the availability of high-bandwidth communication *** techniques are far from realization due to①the lack of utility-grade communica-tion systems in many cases such as secondary(low-voltage)pow-er distribution systems to which EVs are connected,rural ar-eas,remote communities,and islands,and②existing fears and concerns about the data privacy of EV users and cyber-physical *** these cases,appropriate local control schemes are needed to ensure the adequate management of EV charging without violating the grid operation ***,this paper introduces a new communication-less management strategy for EV charging in droop-controlled islanded *** proposed strategy is autonomous,as it is based on the measurement of system frequency and local bus *** proposed strategy implements a social charging fairness policy during periods when the microgrid distributed genera-tors(DGs)are in short supply by allocating more system capaci-ty to the EVs with less charging in the ***,a novel communication-less EV load shedding scheme is incorpo-rated into the management strategy to provide relief to the mi-crogrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG *** simulations demonstrate the superiority of the pro-posed strategy over the state-of-the-art controllers in modulat-ing the EV charging demand to counteract microgrid instability.

关键词： Charging battery management communication-less control droop control electric vehicle islanded microgrid

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Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1893-1932页

作者： Nadeem Salamat Muhammad Kamran Shahzaib Ashraf Ma.al Elzain mohammed Abdulla Rashad Ismail mohammed M.al-Shamiri Institute of Mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of Mathematics Thal University BhakkarPunjab30000Pakistan Department of Mathematics Faculty of Science and ArtsKing Khalid UniversityMuhayl Assir61913Saudi Arabia

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and *** paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse *** it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,*** use rough sets in conjunction with IFSs to develop several fairly aggregation operators and a.alyze their underlying *** present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these *** operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and *** highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making *** use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted ***,we developed a novel technique by combining the IFSs with quaternion *** establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making *** the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately wo

关键词： Intuitionistic fuzzy set quaternion numbers fuzzy logic decision-making rough set

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Experimental and numerical study of effecting core configurations on the static and dynamic behavior of honeycomb plate with aluminum material

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Defence Technology（防务技术） 2024年第9期39卷 177-192页

作者： Nehad Abid allah Hamza Fatima mohammed K.al-Fatlwe Muna.ali Talib Engineering College Al-Qasim Green University51013BabylonIraq Engineering Technical College of al-Najaf Al-Furat Al-Awsat Technical University(ATU)Najaf54003Iraq

The sandwich panel incorporated a honeycomb core,a widely utilized composite structure recognized as a fundamental classification of composite *** a core resembling a honeycomb,possessing thickness and softness,and is flank by rigid face sheets that sandwich various shapes and *** paper presents an examination of the static and dynamic a.alysis of lightweight plates made of aluminum honeycomb sandwich *** sandwich plate samples are 300 mm long,and 300 mm wide,the heights of the core have been varied at four values ranging from 10 to 25 *** honeycomb core is manufactured from aluminum material by using a novel technique namely resistance spot welding(RSW)instead of using adhesive material,which is often used when an industrial flaw is *** optimization based on response surface methodology(RSM)and design of experiment software(DOE)was used to verify the current work.A theoretical examination of the crashworthiness behavior(maximum bending load,maximum deflection)and vibration attributes(natural frequency,damping ratio,transient temporal response)of honeycomb sandwich panels with different design parameters was also carried *** addition,the finite element method-based ANSYS software was used to confirm the theoretical *** findings of the present work showed that the relationship between the natural frequency,core height,and cell size is *** contrast,the relationship between the natural frequency and the thickness of the cell wall is ***,the damping ratio is inversely proportional to the core height and cell size but directly proportional to the thickness of the cell *** study indicates that altering the core height within 10-25 mm leads to a significant increase of 82%in the natural frequency and a notable decrease of 49%in the damping *** findings are based on a specific cell size value of 0.01 m and a cell wall thickness of 0.001 ***,the results indicate

关键词： Honeycomb Load Transient response Free vibration Natural frequency

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An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 88-102页

作者： Changbing Tang Baosen Yang Xiaodong Xie Guanrong Chen mohammed A.a.al-qaness Yang Liu IEEE the College of Physics and Electronic Information Engineering Zhejiang Normal UniversityUniversityJinhua 321004China the School of Mathematical Sciences Zhejiang Normal UniversityJinhua 321004China the Department of Electrical Engineering City University of Hong KongHong KongChina Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Jinhua 321004China

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable *** shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to ***, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

关键词： Federated learning(FL) game theory incentive mechanism machine learning zero-determinant strategy

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