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Preparing and Evaluation of New Nutritious Products from.Quail m.at

Food and Nutrition Sciences 2021年第9期12卷 889-898页

作者： manar m. farag Nadia A. Abd-El-Aziz Afaf m. Ali m.at and Fish Technology Research Departm.nt Food Technology Research Institute Agriculture Research Center Cairo Egypt m.at and Fish Technology Research Departm.nt Food Technology Research Institute Agriculture Research Center Alexandria Egypt

The objective of this study is preparation of new nutritious products from.quail m.at com.ared to other products prepared from.chicken m.at as control and com.ercial products which bought from.superm.rket. The proxim.te com.osition, chem.cal, physical and sensorial properties were evaluated. The different products were prepared as sausage form.quail m.at (SQ), chicken m.at (SC) and com.ercial (SCo), and, kofta from.quail m.at (KQ), chicken m.at (KC) and com.ercial (KCo), and, nuggets from.quail m.at (NQ), chicken m.at (NC) and com.ercial (NCo). The result observed that the chem.cal com.osition of products that prepared from.quail m.at recorded the highest content of protein and ash, on contrary, the lowest content of fat com.ared with products that prepare from.chicken m.at as control or com.ercial. All products that prepared from.quail m.at recorded high content of K, Ca, m., P, Fe, Zn, Se and vitam.n A, Kofta was the highest one followed by nuggets then sausage products. While sausage products that prepared from both quail and chicken meat as control recorded the highest content of vitamin E, followed nuggets and kofta, respectively compared with commercial products. The results indicated decreasing cooking loss after preparing of quail meat products followed by both chicken meat products as control and commercial product, increasing water capacity (WHC) m.ly:"">of KQ and plasticity of SQ and NQ. All products were accepted from.panelists while slightly significant difference am.ng these products (P > 0.05). SC was the highest score in colour, taste, odour, texture and overall acceptability com.ared with SQ and SC

关键词： Quail m.at Chicken m.at Sausage Kofta Nuggets Products m.nerals Vitam.ns Nutritious

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A Novel m.thod for Therm.electric Generator Based on Neural Network

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Com.uters, m.terials & Continua 2022年第10期73卷 2115-2133页

作者： m.ham.ad Saraireh A.m.m.qableh manar Jaradat Om.r A.Saraereh m.chanical Engineering Departm.nt Faculty of EngineeringMutah UniversityKarak61710Jordan Electrom.chanical Engineering Departm.nt Luminus Technical University CollegeAmman11118Jordan Departm.nt of Com.uter Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan Departm.nt of Electrical Engineering Faculty of EngineeringThe Hashemite UniversityZarqa13133Jordan

The growing need for renewable energy and zero carbon dioxide em.ssions has fueled the developm.nt of therm.electric generators with im.roved power generating *** with the endeavor to develop therm.electric m.terials with greater figures of m.rit,the geom.trical and structural optim.zation of therm.electric generators is equally critical for m.xim.m.power output and *** energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the *** have been significant focuses on the developm.nt of therm.electric m.dules for a range of solar,autom.tive,m.litary,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of m.ving *** order to enhance the system.perform.nce of the therm.electric generator,an artificial neural network(ANN)based algorithm.is ***,to achieve high efficiency and system.stability,a buck converter is designed and *** and experim.ntal findings dem.nstrate that the suggested m.thod is viable and available,and that it is alm.st sim.lar to the real value in the steady state with the least power losses,m.king it ideal for vehicle exhaust therm.electric generator ***,the proposed hybrid algorithm.has a high reference value for the developm.nt of a dependable and efficient car exhaust therm.electric generating system.

关键词： Therm.electric system therm.dynam.cs electrom.chanics rotational factors neural networks

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ESSD: Energy Saving and Securing Data Algorithm.for WSNs Security

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Com.uters, m.terials & Continua 2022年第11期73卷 3969-3981页

作者： manar m.Aldaseen Khaled m.m.trouk Laiali H.Alm.zaydeh Khaled m.Elleithy Com.uter Engineering Departm.nt Al-Hussein Bin Talal UniversityMa’anJordan Software Engineering Departm.nt Al-Hussein Bin Talal UniversityMa’anJordan Com.uter Science and Engineering Departm.nt University of BridgeportCTBridgeportUSA

The Wireless Sensor Networks(WSNs)are characterized by their widespread deploym.nt due to low cost,but the WSNs are vulnerable to various types of *** defend against the attacks,an effective security solution is ***,the lim.ts of these networks’battery-based energy to the sensor are the m.st critical im.edim.nts to selecting cryptographic ***,finding a suitable algorithm.that achieves the least energy consum.tion in data encryption and decryption and providing a highly protected system.for data rem.ins the fundam.ntal *** this research,the m.in objective is to obtain data security during transm.ssion by proposing a robust and low-power encryption algorithm.in addition,to exam.ning security algorithm. such as ECC and m.5 based on previous *** this research,the Energy Saving and Securing Data algorithm.ESSD)algorithm.is introduced,which provides the m.ssage Digest 5(m.5)com.utation sim.licity by m.difying the Elliptic Curve Cryptography(ECC)under the prim.ry condition of power *** three algorithm.,ECC,m.5,and ESSD,are applied to Low Energy Adaptive Clustering Hierarchy(LEACH)and Threshold-sensitive Energy Efficient Sensor Network Protocol(TEEN)hierarchical routing algorithm. which are considered the m.st widely used in *** results of security m.thods under the LEACH protocol show that all nodes are dead at 456,496,and 496,respectively,to ECC,m.5,and *** results of security m.thods under the TEEN protocol show that the test ends at 3743,4815,and 4889,respectively,to ECC,m.5,and *** on these results,the ESSD outperform. better in term. of increased security and less power *** addition,it is advantageous when applied to TEEN protocol.

关键词： Cryptography ECC energy consum.tion ESSD LEACH m.5 RSA TEEN WSNs

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An em.irical study on the com.lexity, security and m.intainability of Ethereum.based decentralized applications (DApps)

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Blockchain(Research and Applications) 2023年第2期4卷 28-40页

作者： Noam. Fatim. Sam.een manar H.Alalfi Departm.nt of Com.uter Science Toronto Metropolitan UniversityTorontoON M5B 2K3Canada

The Ethereum.blockchain’s sm.rt contract is a program.able transaction that perform. general-purpose com.utations and can be executed autom.tically on the *** this com.onent,blockchain technology(BT)has grown beyond the scope of cryptocurrencies and can now be applicable in various industries other than *** this paper,we investigated the current trends in Ethereum.based decentralized applications(DApps)to be able to categorize and analyze the DApps to m.asure the com.lexity of sm.rt contracts behind them.their level of security and their correlation to the m.intainability of the *** leveraged the source code analysis,security analysis,and the developm.ntal m.tadata of the DApps to infer this *** on our findings,we concluded that the m.intainability of Ethereum.DApps is proportional to the code size,num.er of functions,and,m.st im.ortantly,the num.er of outgoing invocations and statem.nts in the sm.rt contracts.

关键词： Blockchain technology Ethereum.sm.rt contracts Code m.trics Software com.lexity Software security Software m.intainability Decentralized applications

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Hunger Search Optim.zation with Hybrid Deep Learning Enabled Phishing Detection and Classification m.del

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Com.uters, m.terials & Continua 2022年第12期73卷 6425-6441页

作者： Hadil Shaiba Jaber S.Alzahrani m.jdy m.Eltahir Radwa m.rzouk Heba m.hsen manar Ahm.d Ham.a Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Phishing is one of the sim.lest ways in cybercrim. to hack the reliable data of users such as passwords,account identifiers,bank details,*** general,these kinds of cyberattacks are m.de at users through phone calls,em.ils,or instant *** anti-phishing techniques,currently under use,arem.inly based on source code features that need to scrape the webpage *** third party services,these techniques check the classification procedure of phishing Uniform.Resource Locators(URLs).Even thoughm.chine Learning(m.)techniques have been lately utilized in the identification of phishing,they still need to undergo feature engineering since the techniques are not well-versed in identifying phishing *** trem.ndous growth and evolution of Deep Learning(DL)techniques paved the way for increasing the accuracy of classification *** this background,the current research article presents a Hunger Search Optim.zation with Hybrid Deep Learning enabled Phishing Detection and Classification(HSOHDL-PDC)*** presented HSOHDL-PDC m.del focuses on effective recognition and classification of phishing based on website *** addition,SOHDL-PDC m.del uses character-level em.edding instead of word-level em.edding since the URLs generally utilize words with no ***,a hybrid Convolutional Neural Network-Long Short Term.m.m.ry(HCNN-LSTm.technique is also applied for identification and classification of *** hyperparam.ters involved in HCNN-LSTm.m.del are optim.zed with the help of HSO algorithm.which in turn produced im.roved *** perform.nce of the proposed HSOHDL-PDC m.del was validated using different datasets and the outcom.s confirm.d the suprem.cy of the proposed m.del over other recent approaches.

关键词： Uniform.resource locators phishing cyberattacks m.chine learning deep learning hyperparam.ter optim.zation

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An advanced workflow to com.ress the uncertainties of stochastic distribution of Bahariya reservoir properties using 3D static m.deling:An exam.le from.Heba Oil Fields,Western Desert,Egypt

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Petroleum.Research 2023年第2期8卷 205-216页

作者： Tam.r Hassan Ahm.d m.K.Basal m.ham.ad A.Om.an manar H.m.wafy m.ham.ad A.Sarhan Qarun Petroleum.Com.any(Apache J.V) New MaadiCairo11742Egypt Geology Departm.nt Faculty of ScienceDamietta University34517Egypt

The m.in objective of this paper is to construct a static m.del that com.ress the uncertainties of the stochastic distribution of the reservoir properties of the Bahariya Form.tion in Heba field,at the northeastern portion of the Western *** m.del has been constructed through the integration of the interpretations of the eighteen 2D seism.c sections and the analysis of well logs data for four wells(HEBA 300X,***-E-1X,***-D-1X,and HEBA 10X)drilled in the study *** set of data was im.lem.nted in a harm.nic *** fram.work was the first step created on the basis of the seism.c and well log *** zonation was m.inly m.naged by the m.rine flooding events took place during the Cenom.nian *** trapping faults position uncertainty has been com.ressed through the tying of the seism.c profiles with the identified fault cuts in the well *** porosity spectrum.was broke up into three reservoir *** results showed heterogeneous facies qualities for oil production in specific five zones in the topm.st part of the Bahariya *** effective porosity m.del was generated stochastically considering the norm.l distribution for each reservoir *** saturation was distributed by two m.thods;1)Sequential Gaussian Sim.lation that was co-sim.lated by porosity m.del.2)Log-based saturation height function for each reservoir *** m.thodology provided as accurate as possible estim.tes for the volum. calculation by quantifying the sensitivity of the im.ortant param.ters such as oil ***,the m.del was prepared to be used as a front end for dynam.c sim.lation.

关键词： 3D static m.deling Stochastic distribution Bahariya form.tion Reservoir characterization Heba oil fields

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Big Data Analytics with Artificial Intelligence Enabled Environm.ntal Air Pollution m.nitoring Fram.work

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Com.uters, m.terials & Continua 2022年第11期73卷 3235-3250页

作者： manar Ahm.d Ham.a Hadil Shaiba Radwa m.rzouk Ahm.d Alhindi m.shael m.Asiri Ishfaq Yaseen Abdelwahed m.twakel m.ham.ed Rizwanullah Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia&Research and InnovationSalla Holding LimitedMakkahSaudi Arabia Departm.nt of Com.uter Science College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia

Environm.ntal sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environm.nt particularlyby highly populated countries like India. Due to increased population, thenum.er of vehicles also continues to increase. Each vehicle has its individualem.ssion rate;however, the issue arises when the em.ssion rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in m.chine learning (m.), it is possible to develop predictionapproaches to m.nitor and control pollution using real tim. data. With thedevelopm.nt of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm.shift in how environm.ntal data are em.loyed forsustainable cities and societies, especially by applying intelligent *** this view, this study develops an optim.l AI based air quality prediction andclassification (OAI-AQPC) m.del in big data environm.nt. For handling bigdata from.environm.ntal m.nitoring, Hadoop m.pReduce tool is *** addition, a predictive m.del is built using the hybridization of ARIm.and neural network (NN) called ARIm.-NN to predict the pollution *** im.roving the perform.nce of the ARIm.-NN algorithm. the param.tertuning process takes place using oppositional swallow swarm.optim.zation(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system.(ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experim.ntal analysis is perform.d for highlighting the betterprediction perform.nce of the proposed ARIm.-NN m.thod. The obtainedoutcom.s pointed out the enhanced outcom.s of the proposed OAI-AQPCtechnique over the recent state of art techniques.

关键词： Sustainability environm.ntal air quality predictive m.del pollution m.nitoring statistical m.dels artificial intelligence

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Deep Transfer Learning Driven Autom.ted Fall Detection for Quality of Living of Disabled Persons

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Com.uters, m.terials & Continua 2023年第3期74卷 6719-6736页

作者： Nabil Alm.lki m.im.m.Alnfiai Fahd N.Al-Wesabi m.sfer Alduhayyem.Anwer m.stafa Hilal manar Ahm.d Ham.a King Salm.n Center for Disability Research RiyadhSaudi Arabia Departm.nt of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Departm.nt of Inform.tion Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Departm.nt of Com.uter Science College of Science&ArtsKing Khaled UniversitySaudi Arabia Departm.nt of Com.uter Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

m.bile com.unication and the Internet of Things(IoT)technologies have recently been established to collect data from.hum.n beings and the *** data collected can be leveraged to provide intelligent services through different *** is an extrem. challenge to m.nitor disabled people from.rem.te *** is because day-to-day events like falls heavily result in *** a person with disabilities,a fall event is an im.ortant cause of m.rtality and post-traum.tic ***,detecting the fall events of disabled persons in sm.rt hom.s at early stages is essential to provide the necessary support and increase their survival *** current study introduces a Whale Optim.zation Algorithm.Deep Transfer Learning-DrivenAutom.ted Fall Detection(WOADTL-AFD)technique to im.rove the Quality of Life for persons with *** prim.ry aim.of the presented WOADTL-AFD technique is to identify and classify the fall events to help disabled *** attain this,the proposed WOADTL-AFDm.del initially uses am.dified SqueezeNet feature extractor which proficiently extracts the feature *** addition,the WOADTLAFD technique classifies the fall events using an extrem. Gradient Boosting(XGBoost)*** the presented WOADTL-AFD technique,the WOA approach is used to fine-tune the hyperparam.ters involved in the m.dified SqueezeNet *** proposedWOADTL-AFD technique was experim.ntally validated using the benchm.rk datasets,and the results confirm.d the superior perform.nce of the proposedWOADTL-AFD m.thod com.ared to other recent approaches.

关键词： Quality of living disabled persons intelligent m.dels deep learning fall detection whale optim.zation algorithm

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Novel Im.ge Encryption and Com.ression Schem. for IoT Environm.nt

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Com.uters, m.terials & Continua 2022年第4期71卷 1443-1457页

作者： m.sfer Al Duhayyim.Fahd N.Al-Wesabi Radwa m.rzouk manar Ahm.d Ham.a Anwer m.stafa Hilal m.jdy m.Eltahir Departm.nt of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Departm.nt of Com.uter Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Latest advancem.nts m.de in the processing abilities of sm.rtdevices have resulted in the designing of Intelligent Internet of Things (IoT)environm.nt. This advanced environm.nt enables the nodes to connect, collect, perceive, and exam.ne useful data from.its surroundings. Wireless m.ltim.dia Surveillance Networks (Wm.Ns) form.a vital part in IoT-assistedenvironm.nt since it contains visual sensors that exam.ne the surroundingsfrom.a num.er of overlapping views by capturing the im.ges *** IoT devices generate a m.ssive quantity of digital m.dia, it is thereforerequired to save the m.dia, especially im.ges, in a secure way. In order toachieve security, encryption techniques as well as com.ression techniques areem.loyed to reduce the am.unt of digital data, being com.unicated overthe network. Encryption Then Com.ression (ETC) techniques pave a wayfor secure and com.act transm.ssion of the available data to prevent unauthorized access. With this background, the current research paper presentsa new ETC technique to accom.lish im.ge security in IoT *** proposed m.del involves three m.jor processes nam.ly, IoT-based im.geacquisition, encryption, and com.ression. The presented m.del involves optim.l Signcryption Technique with Whale Optim.zation Algorithm.(Nm.OA)abbreviated as ST-Nm.OA. The optim.l key generation of signcryptiontechnique takes place with the help of Nm.OA. Besides, the presented m.delalso uses Discrete Fourier Transform.(DFT) and m.trix m.nim.zation (m.)algorithm.based com.ression technique. Extensive set of experim.ntal analysis was conducted to validate the effective perform.nce of the proposed *** obtained values infer that the presented m.del is superior in term. of bothcom.ression efficiency and data secrecy in resource-lim.ted IoT environm.nt.

关键词： Data com.ression im.ge security encryption signcryption optim.l key generation

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Optim.l Hybrid Feature Extraction with Deep Learning for COVID-19 Classifications

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Com.uters, m.terials & Continua 2022年第6期71卷 6257-6273页

作者： m.jdy m.Eltahir Ibrahim.Abunadi Fahd NAl-Wesabi Anwer m.stafa Hilal Adil Yousif Abdelwahed m.twakel m.sfer Al Duhayyim.manar Ahm.d Ham.a Departm.nt of Inform.tion System. College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. Prince Sultan UniversityRiyadh11586Saudi Arabia Departm.nt of Com.uter Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Com.uter and IT Sana’a UniversitySana’a61101Yemen Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Faculty of Arts and Science Najran UniversitySharourahSaudi Arabia Departm.nt of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Novel coronavirus 2019(COVID-19)has affected the people’s health,their lifestyle and econom.cal status across the *** application of advanced Artificial Intelligence(AI)m.thods in com.ination with radiological im.ging is useful in accurate detection of the *** also assists the physicians to take care of rem.te villages *** current research paper proposes a novel autom.tedCOVID-19 analysism.thod with the help ofOptim.l Hybrid Feature Extraction(OHFE)and Optim.l Deep Neural Network(ODNN)called OHFE-ODNN from.chest x-ray *** objective of the presented technique is for perform.ng binary and m.lti-class classification of COVID-19 analysis from.chest X-ray *** presented OHFE-ODNN m.thod includes a sequence of procedures such as m.dian Filtering(m.)-based pre-processed,feature extraction and finally,binary(COVID/Non-COVID)and m.lticlass(Norm.l,COVID,SARS)***,in OHFE-based feature extraction,Gray Level Co-occurrence m.trix(GLCm.and Histogram.of Gradients(HOG)are integrated *** presented OHFE-ODNN m.del includes Squirrel Search Algorithm.SSA)for finetuning the param.ters of *** perform.nce of the presented OHFEODNN technique is conducted using chest x-rays *** presented OHFE-ODNN m.thod classified the binary classes effectively with a m.xim.m.recision of 95.82%,accuracy of 94.01%and F-score of 96.61%.Besides,m.ltiple classes were classified proficiently by OHFE-ODNN m.del with a precision of 95.63%,accuracy of 95.60%and an F-score of 95.73%.

关键词： COVID-19 classification deep learning radiological im.ges

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