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A Novel Deep Learning-Based Model for Classification of Wheat Gene Expression

Computer Systems Science & Engineering 2024年第2期48卷 273-285页

作者： Amr ismail WalidHamdy Aya MAl-Zoghby Wael AAwad ahmed ismail ebada Yunyoung Nam Byeong-Gwon Kang Mohamed Abouhawwash Faculty of Science Port Said UniversityPort SaidEgypt Modern Academy for Computer Science and Management Technology Cairo11742Egypt Faculty of Computers and Artificial Intelligence Damietta UniversityNew DamiettaEgypt Department of ICT Convergence Soonchunhyang UniversityAsan31538South Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Deep learning(DL)plays a critical role in processing and converting data into knowledge and *** technologies have been applied in a variety of applications,including image,video,and genome sequence *** deep learning the most widely utilized architecture is Convolutional Neural Networks(CNN)are taught discriminatory traits in a supervised *** comparison to other classic neural networks,CNN makes use of a limited number of artificial neurons,therefore it is ideal for the recognition and processing of wheat gene *** is an essential crop of cereals for people around the *** Genotypes identification has an impact on the possible development of many countries in the agricultural *** quantitative genetics prediction of genetic values is a central *** is an allohexaploid(AABBDD)with three distinct *** sizes of the wheat genome are quite large compared to many other kinds and the availability of a diversity of genetic knowledge and normal structure at breeding lines of wheat,Therefore,genome sequence approaches based on techniques of Artificial Intelligence(AI)are *** paper focuses on using the Wheat genome sequence will assist wheat producers in making better use of their genetic resources and managing genetic variation in their breeding program,as well as propose a novel model based on deep learning for offering a fundamental overview of genomic prediction theory and current *** this paper,the hyperparameters of the network are optimized in the CNN to decrease the requirement for manual search and enhance network performance using a new proposed model built on an optimization algorithm and Convolutional Neural Networks(CNN).

关键词： Gene expression convolutional neural network optimization algorithm genomic prediction wheat

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Handling Big Data in Relational Database Management Systems

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Computers, Materials & Continua 2022年第9期72卷 5149-5164页

作者： Kamal ElDahshan Eman Selim ahmed ismail ebada Mohamed Abouhawwash Yunyoung Nam Gamal Behery Faculty of Science Al-Azhar UniversityCairoEgypt Faculty of Computer and Artificial Intelligence Damietta UniversityEgypt Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Currently, relational database management systems (RDBMSs)face different challenges in application development due to the massive growthof unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, whichdo not adhere to the relational model. The migration from relational databasesto NoSQL databases is challenging due to the data complexity. This study aimsto enhance the storage performance of RDBMSs in handling a variety of *** paper presents two approaches. The first approach proposes a convenientrepresentation of unstructured data storage. Several extensive experimentswere implemented to assess the efficiency of this approach that could resultin substantial improvements in the RDBMSs storage. The second approachproposes using the JavaScript Object Notation (JSON) format to representmultivalued attributes and many to many (M:N) relationships in relationaldatabases to create a flexible schema and store semi-structured data. Theresults indicate that the proposed approaches outperform similar approachesand improve data storage performance, which helps preserve software stabilityin huge organizations by improving existing software packages whose replacement may be highly costly.

关键词： Big data RDBMS NoSQL DBMSs MongoDB MySQL unstructured data semi-structured data

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Applying Apache Spark on Streaming Big Data for Health Status Prediction

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Computers, Materials & Continua 2022年第2期70卷 3511-3527页

作者： ahmed ismail ebada Ibrahim Elhenawy Chang-Won Jeong Yunyoung Nam Hazem Elbakry Samir Abdelrazek Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computers and InformationEl-Zagazig UniversityZagazigSharqiyah44519Egypt Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Big data applications in healthcare have provided a variety of solutions to reduce costs,errors,and *** work aims to develop a real-time system based on big medical data processing in the cloud for the prediction of health *** the proposed scalable system,medical parameters are sent to Apache Spark to extract attributes from data and apply the proposed machine learning *** this way,healthcare risks can be predicted and sent as alerts and recommendations to users and healthcare *** proposed work also aims to provide an effective recommendation system by using streaming medical data,historical data on a user’s profile,and a knowledge database to make themost appropriate real-time recommendations and alerts based on the sensor’s *** proposed scalable system works by tweeting the health status attributes of *** cloud profile receives the streaming healthcare data in real time by extracting the health attributes via a machine learning prediction algorithm to predict the users’health ***,their status can be sent on demand to healthcare ***,machine learning algorithms can be applied to stream health care data from wearables and provide users with insights into their health *** algorithms can help healthcare providers and individuals focus on health risks and health status changes and consequently improve the quality of life.

关键词： Big data streaming processing healthcare data machine learning IoT data processing Apache Spark

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A New Generative Mathematical Model for Coverless Steganography System Based on Image Generation

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Computers, Materials & Continua 2023年第3期74卷 5087-5103页

作者： Al-Hussien Seddik Mohammed Salah Gamal Behery ahmed El-harby ahmed ismail ebada Sokea Teng Yunyoung Nam Mohamed Abouhawwash Department of Computer Science Faculty of ScienceMinia UniversityMiniaEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its ***,researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it;this is called the stego *** paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response(QR)code and maze game image *** system consists of two *** first component contains two processes,encryption process,and hiding *** encryption process encrypts secret message bits in the form of a semi-QR code image whereas the hiding process conceals the pregenerated semi-QR code in the generated maze game *** the other hand,the second component contains two processes,extraction and decryption,which are responsible for extracting the semi-QR code from the maze game image and then retrieving the original secret message from the extracted semi-QR code image,*** results were obtained using the bit error rate(BER)*** results confirmed that the system achieved high hiding capacity,good performance,and a high level of robustness against attackers compared with other coverless steganography methods.

关键词： Coverless steganography data hiding information security QR code maze game

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An Automatic Deep Neural Network Model for Fingerprint Classification

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Intelligent Automation & Soft Computing 2023年第5期36卷 2007-2023页

作者： Amira Tarek Mahmoud Wael AAwad Gamal Behery Mohamed Abouhawwash Mehedi Masud Hanan Aljuaid ahmed ismail ebada Department of Computer Science Faculty of SciencePort Said UniversityPort SaidEgypt Department of Computer Science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI 48824USA Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)P.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaEgypt

The accuracy ofﬁngerprint recognition model is extremely important due to its usage in forensic and securityﬁ***ﬁngerprint recognition system has particular network architecture whereas many other networks achieve higher *** solve this problem in a uniﬁed model,this paper proposes a model that can automatically specify ***,it is called an automatic deep neural net-work(ADNN).Our algorithm can specify the appropriate architecture of the neur-al network used and some signiﬁcant parameters of this *** parameters are the number ofﬁlters,epochs,and *** guarantees the high-est accuracy by updating itself until achieving 99%accuracy then it stops and out-puts the ***,this paper proposes an end-to-end methodology for recognizing a person’s identity from the inputﬁngerprint image based on a resi-dual convolutional neural *** is a complete system and is fully automated whether in the features extraction stage or the classiﬁcation *** goal is to automate thisﬁngerprint recognition system because the more automatic the sys-tem is,the more time and effort it *** model also allows users to react by inputting the initial values of these ***,the model updates itself until itﬁnds the optimal values for the parameters and achieves the best *** advantage of our algorithm is that it can recognize people from their thumb and otherﬁngers and its ability to recognize distorted *** algo-rithm achieved 99.75%accuracy on the publicﬁngerprint dataset(SOCOFing).This is the best accuracy compared with other models.

关键词： Automatic system ﬁngerprint classiﬁcation residual networks deep learning

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Coverless Image Steganography System Based on Maze Game Generation

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Intelligent Automation & Soft Computing 2023年第11期38卷 125-138页

作者： Al Hussien Seddik Saad Mohammed S.Reda GamalM.Behery ahmed A.El-harby Mohammed Baz Mohamed Abouhawwash ahmed ismail ebada Department of computer science Faculty of ScienceMinia UniversityShalabyMiniaEgypt Department of computer science Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaDamiettaEgypt Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityP.O.Box 11099Taif21994Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI48824USA Department of Information Systems Faculty of Computers and Artificial IntelligenceDamietta UniversityNew DamiettaDamiettaEgypt

The trend of digital information transformation has become a topic of *** data are threatening;thus,protecting such data from attackers is considered an essential ***,a new methodology for data concealing has been suggested by researchers called coverless *** steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an *** paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the other traditional *** system uses the secret message to generate the stego image in the form of one of the Intelligence Quotient(IQ)games,the ***,a full grid is generated with several specific rows and columns determined from the number of bits of the secret ***,these bits are fed to the full grid to form the maze game stego ***,the generated maze game stego image is sent to the *** experimental results,using the Bit Error Rate(BER),were conducted,and confirmed the strength of this system represented by a high capacity,perfect performance,robustness,and stronger hiding system compared with existing coverless steganography systems.

关键词： Coverless data hiding digital image steganography intelligence quotient games maze game

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Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

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Computers, Materials & Continua 2024年第5期79卷 2771-2793页

作者： Zohaib Ahmad Khan Yuanqing Xia ahmed Khan Muhammad Sadiq Mahmood Alam Fuad AAwwad Emad A.A.ismail School of Automation Beijing Institute of TechnologyBeijing100081China Department of Computer Science and Technology University of Science and Technology BannuKPKBannu28100Pakistan School of Computer Science and Engineering Central South UniversityChangsha410083China Department of Quantitative Analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

关键词： Emotional assessment regional dialects SentiWordNet naive bayesian technique lexicons software engineering user feedback

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Primary gastroduodenal tuberculosis presenting as gastric outlet obstruction:A case report and review of literature

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World Journal of Clinical Cases 2024年第8期12卷 1536-1543页

作者： Abdihamid Mohamed Ali Yahye Garad Mohamed Abdirahman ahmed Mohamud Abdulkadir Nor Mohamed Mohamed Rage ahmed ismail Mohamud Abdullahi Tuba Saydam Department of General Surgery Mogadishu Somali Turkey Recep Tayyip Erdogan Training and Research HospitalMogadishu 2526Somalia Department of Radiology Mogadishu Somali TurkeyTraining and Research HospitalMogadishu 2526Somalia Department of Pathology Mogadishu Somali Turkey Recep Tayyip Erdogan Training and Research HospitalMogadishu 2526Somalia

BACKGROUND Mycobacterium tuberculosis(TB)is the causative agent of TB,a chronic granulo-matous *** disease is prevalent in low-income countries,posing a significant global health *** TB is one of the three *** disease can mimic other intra-abdominal conditions,leading to delayed diagnosis owing to the absence of specific *** gastric outlet obs-truction(GOO)remains a frequent complication,its incidence has declined with the advent of proton pump inhibitors and Helicobacter pylori eradication *** TB can cause upper gastrointestinal hemorrhage,obstruction,and malignancy-like *** SUMMARY A 23-year-old male presented with recurrent epigastric pain,distension,nausea,vomiting,and weight loss,prompting a referral to a gastroenterologist *** examination revealed distorted gastric mucosa and signs of chronic ***,treatment was interrupted,possibly owing to vomiting or comorbidities such as human immunodeficiency virus infection or *** surgical intervention revealed a dilated stomach and diffuse thickening of the duodenal *** revealed gastric wall effacement with *** Primary gastric TB is rare,frequently leading to *** its rarity,suspicions should be promptly raised when encountering relevant symptoms,often requiring surgical intervention for diagnosis and treatment.

关键词： Tuberculosis Gastrointestinal tuberculosis Gastric outlet obstruction Gastroduodenal tuberculosis Case report

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria ahmed Abu-Khadrah Mahamod ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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A Survey on Visualization-Based Malware Detection

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Journal of Cyber Security 2022年第3期4卷 153-168页

作者： Ahmad Moawad ahmed ismail ebada Aya M.Al-Zoghby Computer Science Department Faculty of Computers and Artificial IntelligenceDamiettaNew Damietta34517Egypt

In computer security,the number of malware threats is increasing and causing damage to systems for individuals or organizations,necessitating a new detection technique capable of detecting a new variant of malware more efficiently than traditional anti-malware *** antimalware software cannot detect new malware variants,and conventional techniques such as static analysis,dynamic analysis,and hybrid analysis are time-consuming and rely on domain ***-based malware detection has recently gained popularity due to its accuracy,independence from domain experts,and faster detection ***-based malware detection uses the image representation of the malware binary and applies image processing techniques to the *** paper aims to provide readers with a comprehensive understanding of malware detection and focuses on visualization-based malware detection.

关键词： Malware detection malware image malware classification visualization-based detection survey

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