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K-Banhatti Sombor Invariants of Certain Computer Networks

Computers, Materials & Continua 2022年第10期73卷 15-31页

作者： Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad Usman Ashraf ahmed mohammed Alghamdi Adel A.Bahaddad Khalid ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Mathematics University of SialkotSialkot51013Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Any number that can be uniquely determined by a graph is called a graph *** the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation ***,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular *** this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or *** study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced *** deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis.

关键词： Bridge networks invariants k-banhatti sombor indices maple network graph molecular graph

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Restoration and Conservation of Deteriorated Arid Land by a Native Thorny Shrub Lycium shawii

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Journal of Agricultural Science and Technology(A) 2017年第2期7卷 100-106页

作者： Modi mohammed ahmed ali mohammed AI-Dousari Crisis Decision Program Environment and Life Science Research Center Kuwait Institute for Scientific Research P.O. Box 24885Safat 13109 Kuwait

Land degradation is of great concern in the desert environment of Kuwait, as it has a negative impact on the natural resources. In response to this situation, Kuwait conserves their natural environment by setting aside areas of significant natural ecosystem, such as wild life center at the Liyah area. The area suffered during the past four decades from severe environmental pressures due to the excessive exploitation of natural resources of sand and gravel as well as overgrazing and military activities. Re-vegetation and restoration programs were applied in the degraded areas in Liyah in December 2003. A large variety of native plants were used for the restoration, however, in this research, only one native perennial drought resistant plant Lycium shawii （Awsaj） was highlighted. Tissue cultured thorny shrub planted at experimental site showed high adaptation on gravel hill side with harsh field condition. Their survival rate was 100% under drip irrigation only 10% was the mortality rate due to improper fixation of irrigation system. The average length of the main stem and the number of branches gradually increased by year from 42 cm with three branches in 2011 to 170 cm with seven branches in 2014. Since Lycium shrubs have the ability to grow in severely degraded areas, with extreme condition of prolonged drought, high temperature and poor nutrient soil as well as their ability to form nabkha, it is considered to be most suitable shrub used for rehabilitation program at Liyah area.

关键词： Degraded lands restoration program thomy shrub Lycium shawii.

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Analysis of BrainMRI: AI-Assisted Healthcare Framework for the Smart Cities

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Intelligent Automation & Soft Computing 2023年第2期35卷 1843-1856页

作者： Walid El-Shafai Randa ali ahmed Sedik Taha El-Sayed Taha mohammed Abd-Elnaby Fathi E.Abd El-Samie Department Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of ROBOTICS and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The use of intelligent machines to work and react like humans is vital in emerging smart ***-aided analysis of complex and huge MRI(Mag-netic Resonance Imaging)scans is very important in healthcare *** AI(Artiﬁcial Intelligence)driven healthcare applications,tumor detection is one of the contemporary researchﬁelds that have become attractive to *** are several modalities of imaging performed on the brain for the pur-pose of tumor *** paper offers a deep learning approach for detecting brain tumors from MR(Magnetic Resonance)images based on changes in the division of the training and testing data and the structure of the CNN(Convolu-tional Neural Network)*** proposed approach is carried out on a brain tumor dataset from the National Centre of Image-Guided Therapy,including about 4700 MRI images of ten brain tumor cases with both normal and abnormal *** dataset is divided into test,and train subsets with a ratio of the training set to the validation set of 70:*** main contribution of this paper is introdu-cing an optimum deep learning structure of CNN *** simulation results are obtained for 50 epochs in the training *** simulation results reveal that the optimum CNN architecture consists of four layers.

关键词： Healthcare smart cities clinical automation CNN machine learning brain tumor medical diagnosis

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Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

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Intelligent Automation & Soft Computing 2023年第5期36卷 1915-1930页

作者： Rab Nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf ahmed mohammed Alghamdi Adel ABahaddad Khalid ali Almarhabi Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science and IT Islamia University BahawalpurPakistan Department of Software Engineering Superior University Lahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be deﬁned by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

关键词： Leaching fraction saline soil evapotranspiration machine learning calibrated evapotranspiration artiﬁcial intelligence blaney criddle method

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CryptoNight Mining Algorithm with YAC Consensus for Social Media Marketing Using Blockchain

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Computers, Materials & Continua 2022年第5期71卷 3921-3936页

作者： Anwer Mustafa Hil Fahd N.Al-Wesabi Hadeel Alsolai Ola Abdelgney Omer ali Nadhem Nemri Manar ahmed Hamza Abu Sarwar Zamani mohammed Rizwanullah Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia&Faculty of Computer and ITSana’a UniversityYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia

Social media is a platform in which user can create,share and exchange the knowledge/*** media marketing is to identify the different consumer’s demands and engages them to create marketing *** popular social media platforms are Microsoft,Snapchat,Amazon,Flipkart,Google,eBay,Instagram,Facebook,Pin interest,and *** main aim of social media marketing deals with various business partners and build good relationship with millions of customers by satisfying their *** technology is replacing old approaches in the social media marketing to new technology-based ***,this disruptive technology creates some issues like fake news,insecure,inconsistency,inaccuracy and so *** issues contribute economic instability in the society,diminishing the level of *** overcome these issues,this paper we present blockchain as disruptive technology for social media *** plays a vital role on social media marketing by providing secure to the company page in the *** properties of disruptive potential of blockchain on social media marketing is transparency,security,reliability and *** paper presents a new framework for disruptive technology in blockchain social media marketing using fusion of CryptoNight mining algorithm with YAC consensus algorithm[BCDSMM-CNYAC].This mining algorithm provides high CPU efficiency,high dimensionality of secure and detecting falsifying data attack in the social media *** the data analysis we proposed ANOVA analysis method regarding to the factors of age,time,frequency visiting times of social media *** reliability analysis of data Cronbach’s alpha tests are implemented.

关键词： Cryptonight disruptive technology smart contracts social media security YAC

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Impedance spectroscopy and DFT/TD-DFT studies of diyttrium trioxide for optoelectronic fields

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Journal of Rare Earths 2023年第4期41卷 605-612页

作者： ali A.Alkathiri A.A.Atta Moamen S.Refat Sonam Shakya A.M.Hassanien Saud A.Algarni Emad M.A.ahmed Sultan E.Alomariy mohammed Alsawat Norah Algethami Department of Physics College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Chemistry Aligarh Muslim UniversityAligarh202002India Department of Physics Faculty of Science and Humanity Studies at Al-QuwayiyahShaqra UniversityAl-Quwayiyah11971Saudi Arabia

Yttrium(Ⅲ)oxide or so-called diyttrium trioxide(Y_2O_3)is an excellent candidate ceramic material for optoelectronic ***,electrical conductivity,and dielectric relaxation properties of bulk yttrium(Ⅲ)oxide were studied.X-ray diffraction(XRD)results indicate that the yttrium(Ⅲ)oxide compound has a crystalline cubic *** transform infrared(FTIR)technique was used to ascertain the chemical structure of the yttrium(Ⅲ)oxide *** spectroscopy was used to analyze frequency-dependent electrical properties as a function of temperature in the range of 303-423 K and frequency range of 0.1 Hz-2 *** spectroscopy parameters such as dielectric constant,dielectric loss,loss factor,electric modulus,and complex impedance of the yttrium(Ⅲ)oxide compound were *** Nyquist plot describes the complex impedance of the yttrium(Ⅲ)oxide for different *** universal Jonscher's power law was used for the analysis of the complex electrical conductivity of the yttrium(Ⅲ)oxide *** is found that the real(σ')and imaginary(σ")parts of the complex conductivity increase with increasing *** exponent frequency(s)equals unity,which confirms that the predominant conduction mechanism is a nearly constant loss(NCL)***/TD-DFT studies using B3LYP/LanL2DZ level of theory were used to provide comparable theoretical data and electronic energy gap of HOMO→LUMO.

关键词： Yttrium(Ⅲ)oxidel Impedance spectroscopy DFT/TD-DFT Rare earths

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Evaluation of the chemical constituents,antioxidant and enzyme inhibitory activities of six Yemeni green coffee beans varieties

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Food Bioscience 2022年第2期46卷 1006-1013页

作者： Ammar mohammed ahmed ali Sakina Yagi ahmed A.Qahtan Abdurrahman A.Alatar Simone Angeloni Filippo Maggi Giovanni Caprioli Eslam M.Abdel-Salam Kouadio Ibrahime Sinan Gokhan Zengin Department of Biology Faculty of EducationHajji UniversityHajjahYemen Botany Department Faculty of ScienceUniversity of KhartoumSudan Department of Botany&Microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Chemistry Interdisciplinary Project(ChIP) School of PharmacyUniversity of CamerinoVia Madonna delle Carceri 9/BI62032CamerinoMCItaly Physiology and Biochemistry Laboratory Department of BiologyScience FacultySelcuk UniversityCampus42103KonyaTurkey

Coffee arabica *** an economical crop cultivated in many countries including *** present study evaluated the phytochemical contents of the methanolic extracts,prepared by maceration,of six Yemeni green coffee beans varieties namely Esmaeli,Hamadi,Harazi,Mattari,Odaini and ***(phosphomolybdenum,antiradical,reducing power and ferrous chelating),and enzyme inhibition activity of the extracts against acetylcholinesterase butyrylcholinesterase,tyrosinase,α-glucosidase,andα-amylase were also *** of total phenols revealed that all green beans varieties were richer in their total polyphenolic(63.77-110.98 mg gallic acid equivalent per g of extract)content than their flavonoids one(2.86-5.57 mg rutin equivalent per g of extract).HPLC-MS/MS analysis of 30 selected bioactive compounds showed that all varieties had the same types of phytoconstituents with differences in their relative ***(1613.89-2466.38μg/g)followed by 5-caffeoylquinic acid(1017.63-1313.39μg/g)were the dominant compounds in all varieties with caffeine more abundant in Esmaeli variety while 5-caffeoylquinic acid in Odaini *** varieties displayed a pronounced antioxidant property in all the in vitro assays with Odaini variety significantly(p<0.05)exerted the highest anti-DPPH radicals(253.96 mg Trolox equivalent(TE)/g),metal chelating(19.73 mg Disodium edetate equivalents/g),Cu^(2+)(441.11 mg TE/g)and Fe3+(221.04 mg TE/g)reducing ***,the majority of green coffee beans varieties showed comparable enzyme inhibition property with highest activity recorded against tyrosinase(39.35-46.96 mg kojic acid equivalents/g)and acetylcholinesterase(1.80-2.17 mg galanthamine equivalents/g)*** conclusion,all Yemeni green coffee beans varieties have proven to be rich source of biochemicals with beneficial impact on human health and could be of significant applications in food,pharmaceutical and cosmetics industry.

关键词： Yemeni coffee Phytoconstituents Green coffee HPLC-MS/MS Antioxidants Enzyme inhibitory properties

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Severity Based Light-Weight Encryption Model for Secure Medical Information System

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Computers, Materials & Continua 2023年第3期74卷 5691-5704页

作者： Firas Abedi Subhi R.M.Zeebaree Zainab Salih Ageed Hayder M.A.Ghanimi ahmed Alkhayyat mohammed A.M.Sadeeq Sarmad Nozad Mahmood ali S.Abosinnee Zahraa H.Kareem ali Hashim Abbas Waleed Khaild Al-Azzawi Mustafa Musa Jaber mohammed Dauwed Department of Mathematics College of EducationAl-Zahraa University for WomenKarbalaIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Biomedical Engineering Department College of EngineeringUniversity of Warith Al-AnbiyaaKarbalaIraq College of Technical Engineering The Islamic UniversityNajafIraq ITM Department Technical College of AdministrationDuhok Polytechnic UniversityDuhokIraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq Altoosi University College NajafIraq Department of Medical Instrumentation Techniques Engineering Al-Mustaqbal University CollegeHillah51001Iraq College of Information Technology Imam Ja’afar Al-Sadiq UniversityAl-Muthanna66002Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi UniversityBagdadIraq Department of Medical Instruments Engineering Techniques Al-Turath University CollegeBaghdad10021Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi UniversityBaghdad10021Iraq Department of Medical Instrumentations Techniques Engineering Dijlah University CollegeBaghdadIraq

As the amount of medical images transmitted over networks and kept on online servers continues to rise,the need to protect those images digitally is becoming increasingly ***,due to the massive amounts of multimedia and medical pictures being exchanged,low computational complexity techniques have been *** commonly used algorithms offer very little security and require a great deal of communication,all of which add to the high processing costs associated with using ***,a deep learning classifier is used to classify records according to the degree of concealment they *** images that aren’t needed can be saved by using this method,which cuts down on security *** is one of the most effective methods for protecting medical images after this *** and dispersion are two fundamental encryption processes.A new encryption algorithm for very sensitive data is developed in this *** splitting with image blocks is nowdeveloped by using Zigzag patterns,rotation of the image blocks,and random permutation for scrambling the *** that,this research suggests a Region of Interest(ROI)technique based on selective picture *** the first step,we use an active contour picture segmentation to separate the ROI from the Region of Background(ROB).Permutation and diffusion are then carried out using a Hilbert curve and a Skew Tent *** all of the blocks have been encrypted,they are combined to create encrypted *** investigational analysis is carried out to test the competence of the projected ideal with existing techniques.

关键词： Deep learning encryption medical images scrambling security skew tent map rotation zigzag pattern

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The Spleen and Sickle Cell Anemia: A Contrast Enhanced Computerized Tomography Based Study

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Open Journal of Radiology 2016年第3期6卷 168-180页

作者： Malaz mohammed ali Omer ahmed Caroline Edward Ayad Sudan University of Science and Technology College of Medical Radiological Science Khartoum Sudan

The spleen is one of the most frequently affected organs in sickle cell anemia (SCA). This study aims to characterize the spleen in sickle cell anemia patients using contrast enhanced computerized tomography scanning (CECT). 67 patients with SCA from different Saudi Arabian areas were enrolled;ages are ranged from 10 months to 28 years old. The spleen was assessed with CT for abdominal pain and/or unexplained fever. The evaluation was done at different contrast enhancement scanning phases. The study showed that the least number of affected patients was from Eastern Saudi Arabia (1.5%) followed by Asseer (16.4%) then Gazan representing 82.1%. The most common type of SCA affected the Saudi children is Hemoglobin SS Disease (Hb SS) constituting 41 (61.2%). The spleen size, lymph nodes size, spleen Hounsfield (HU), splenic vein diameter and the correlation with the associated findings were evaluated for all of the patients. In children affected with SCA: 26 (38.8%) have splenomegaly, 18 (26.9%) have atrophied spleen and 2 (3.0%) are with very small tissue like structure. Lesions found in the spleen were abscess, infarction, cyst, and calcifications. At the spleen hilum region;dilated splenic vein, presence of multiple collaterals, and thrombus were also been detected. Significantly correlations were noticed between lesions type, child age, enlargement of spleen and splenic lymph nodes at P ≤ 0.033, P ≤ 0.010 and P ≤ 0.012 respectively and showed an evidence that the reduction of the HU and advanced age have significant relation with changing of the spleen size at P ≤ 0.004 and P ≤ 0.000 respectively. Spleen lesions’ enhancement pattern is well emerged in both venous and delay phase and it was significantly related with the scanning phase at P ≤ 0.000 and with different types of SCA at P ≤ 0.037, and P ≤ 0.055 in venous and delay phase in respectively. CECT offers a number of morphological criteria that can be applied to differentiate hypodense lesions of the spleen in S

关键词： Spleen Sickle Cell Disease Computerized Tomography

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Fusion-Based Deep Learning Model for Automated Forest Fire Detection

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Computers, Materials & Continua 2023年第10期77卷 1355-1371页

作者： Mesfer Al Duhayyim Majdy M.Eltahir Ola Abdelgney Omer ali Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Anwer Mustafa Hilal Manar ahmed Hamza mohammed Rizwanullah Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Technology College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

Earth resource and environmental monitoring are essential areas that can be used to investigate the environmental conditions and natural resources supporting sustainable policy development,regulatory measures,and their implementation elevating the ***-scale forest fire is considered a major harmful hazard that affects climate change and life over the ***,the early identification of forest fires using automated tools is essential to avoid the spread of fire to a large ***,this paper focuses on the design of automated forest fire detection using a fusion-based deep learning(AFFD-FDL)model for environmental *** AFFDFDL technique involves the design of an entropy-based fusion model for feature *** combination of the handcrafted features using histogram of gradients(HOG)with deep features using SqueezeNet and Inception v3 ***,an optimal extreme learning machine(ELM)based classifier is used to identify the existence of fire or *** order to properly tune the parameters of the ELM model,the oppositional glowworm swarm optimization(OGSO)algorithm is employed and thereby improves the forest fire detection performance.A wide range of simulation analyses takes place on a benchmark dataset and the results are inspected under several *** experimental results highlighted the betterment of the AFFD-FDL technique over the recent state of art techniques.

关键词： Environment monitoring remote sensing forest fire detection deep learning machine learning fusion model

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