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Computers, materials & Continua 2024年第3期78卷 3129-3150页

作者： Awais Ahmad Sohail Jabbar Sheeraz Akram Anand Paul Umar Raza nuha mohammed Alshuqayran College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudia Arabia 2 School of Computer Science and EngineeringKyungpook National UniversityDaegu41566South Korea 3 Department of EngineeringManchester Metropolitan UniversityManchesterM156BHUK

This paper presents an innovative approach to enhance the querying capability of ChatGPT,a conversational artificial intelligence model,by incorporating voice-based interaction and a convolutional neural network(CNN)-based impaired vision detection *** proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice ***,a CNN-based model is employed to detect impairments in user vision,enabling the system to adapt its responses and provide appropriate *** research tackles head-on the challenges of user experience and inclusivity in artificial intelligence(AI).It underscores our commitment to overcoming these obstacles,making ChatGPT more accessible and valuable for a broader *** integration of voice-based interaction and impaired vision detection represents a novel approach to conversational ***,this innovation transcends novelty;it carries the potential to profoundly impact the lives of users,particularly those with visual *** modular approach to system design ensures adaptability and scalability,critical for the practical implementation of these ***,the solution places the user at its *** responses for those with visual impairments demonstrates AI’s potential to not only understand but also accommodate individual needs and preferences.

关键词： Accessibility in conversational AI CNN-based impair vision detection ChatGPT voice-based interaction recommender system

Hematological Alterations in an Eastern Sudanese Chronic Kidney Disease Patient Population

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Open Journal of Urology 2024年第6期14卷 359-367页

作者： mohammed Omer Abaker Gibreel Sundus Kamal Ibrahim Wijdan Abdel Aziz Hassan manar Yahia mahjoub Leyla mohammed Kheir Hamid Hibatellah majzoub Abbas nuha Fouzi mohammed Secretariat of Academic Affairs Port Sudan Ahlia University Port Sudan Sudan Department of Hematology and Immunohematology College of Graduate Studies Port Sudan Ahlia University Port Sudan Sudan

Background: Chronic Kidney Disease (CKD), associated with a slow and progressive loss of kidney function over a period of several years, is an important clinical disaster with an increasing rate of morbidity and mortality especially in the least developed countries. many hematological parameters are thought to alter dramatically during the course of the disease. These include white blood cells, red blood cells, and platelets. methods: We tried, retrospectively, to evaluate the peripheral blood hematological alterations in a group of patients undergoing hemodialysis in an eastern Sudan dialysis center to add local medical information. Results: Anemia (Low hemoglobin and hematocrit) was detected in 94% of the patients’ group. mean Erythrocyte count (3.32vs.4.76 (×109/L)), Hemoglobin concentration (9.4vs.13 (g/dl)), Hematocrit (28.7vs.38.7 (L/L)) and platelet count (296 vs. 238 (×109/L)) were significantly lower in the patients’ group than in the control group (P-values Conclusion: Five out of eight studied parameters (Red cell count, hemoglobin, hematocrit, mean cell hemoglobin concentration, and platelets count) have shown a significant alteration in CKD patients. As the complete blood count (CBC) test is the most utilized test in clinical laboratory practice, these alterations may be considered as early indicators for CKD. Furthermore, all patients with CKD must be routinely checked for these alterations.

关键词： Chronic Kidney Disease Chronic Renal Failure Hematological Alterations CBC Eastern Sudan Hemodialysis

Improving Performance of Recurrent Neural Networks Using Simulated Annealing for Vertical Wind Speed Estimation

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Energy Engineering 2023年第4期120卷 775-789页

作者： Shafiqur Rehman HilalH.nuha Ali Al Shaikhi Satria Akbar mohamed mohandes Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) KFUPMDhahran31261Saudi Arabia HUmIC Engineering School of ComputingTelkom UniversityBandung40257Indonesia Electrical Engineering Department King Fahd University of Petroleum&Minerals(KFUPM)Dhahran31261Saudi Arabia

An accurate vertical wind speed(WS)data estimation is required to determine the potential for wind farm *** general,the vertical extrapolation of WS at different heights must consider different parameters fromdifferent locations,such as wind shear coefficient,roughness length,and atmospheric *** novelty presented in this article is the introduction of two steps optimization for the Recurrent Neural Networks(RNN)model to estimate WS at different heights using measurements from lower *** first optimization of the RNN is performed to minimize a differentiable cost function,namely,mean squared error(mSE),using the Broyden-Fletcher-Goldfarb-Shanno ***,the RNN is optimized to reduce a non-differentiable cost function using simulated annealing(RNN-SA),namely mean absolute error(mAE).Estimation ofWS vertically at 50 m height is done by training RNN-SA with the actualWS data a 10–40 m *** estimatedWS at height of 50 m and the measured WS at 10–40 heights are further used to train RNN-SA to obtain WS at 60 m *** procedure is repeated continuously until theWS is estimated at a height of 180 *** RNN-SA performance is compared with the standard RNN,multilayer Perceptron(mLP),Support Vector machine(SVm),and state of the art methods like convolutional neural networks(CNN)and long short-term memory(LSTm)networks to extrapolate theWS *** estimated values are also compared with realWS dataset acquired using LiDAR and tested using four error metrics namely,mean squared error(mSE),mean absolute percentage error(mAPE),mean bias error(mBE),and coefficient of determination(R2).The numerical experimental results show that the mSE values between the estimated and actualWS at 180mheight for the RNN-SA,RNN,mLP,and SVm methods are found to be 2.09,2.12,2.37,and 2.63,respectively.

关键词： Vertical wind speed estimation recurrent neural networks simulated annealing multilayer perceptron support vector machine

Optimal Bottleneck-Driven Deep Belief Network Enabled malware Classification on IoT-Cloud Environment

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Computers, materials & Continua 2023年第2期74卷 3101-3115页

作者： mohammed maray Hamed Alqahtani Saud S.Alotaibi Fatma S.Alrayes nuha Alshuqayran mrim m.Alnfiai Amal S.mehanna mesfer Al Duhayyim Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of information systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Digital media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

Cloud Computing(CC)is the most promising and advanced technology to store data and offer online services in an effective *** such fast evolving technologies are used in the protection of computerbased systems from cyberattacks,it brings several advantages compared to conventional data protection *** of the computer-based systems that effectively protect the data include Cyber-Physical Systems(CPS),Internet of Things(IoT),mobile devices,desktop and laptop computer,and critical *** software(malware)is nothing but a type of software that targets the computer-based systems so as to launch cyberattacks and threaten the integrity,secrecy,and accessibility of the *** current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity malware Classification(OBDDBNCmC)*** presentedOBDDBN-CmCmodel intends to recognize and classify the malware that exists in IoT-based cloud *** attain this,Zscore data normalization is utilized to scale the data into a uniform *** addition,BDDBN model is also exploited for recognition and categorization of *** effectually fine-tune the hyperparameters related to BDDBN model,GrasshopperOptimizationAlgorithm(GOA)is *** scenario enhances the classification results and also shows the novelty of current *** experimental analysis was conducted upon OBDDBN-CmC model for validation and the results confirmed the enhanced performance ofOBDDBNCmC model over recent approaches.

关键词： malware detection security Internet of Things cloud computing machine learning parameter adjustment

Formation and Biomimetic Deposition of Bone-like Hydroxyapatite on Wollastonite-gypsum Composites

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Journal of Bionic Engineering 2018年第5期15卷 894-906页

作者： Yaser Greish nuha Attia Abdel-Hamid mourad Department of Chemistry College of Science United Arab Emirates University AI Ain UAE Department of Ceramics National Research Centre Cairo Egypt Department of mechanical Engineering College of Engineering United Arab Emirates University Al Ain UAE mechanical Design Department Faculty of Engineering at Mataria Helwan University Cairo Egypt

Bone cements are often used for bone repair and fixation. The main objective of formulating a bone cement is to achieve structure and properties similarity to bone. In addition, bioactivity of a bone cement provides a major advantage that helps achieving better binding and interaction with the surrounding tissues. In the current study, gypsum was used as a matrix for a composite that comprises highly crys- talline prestine and acid-treated wollastonite （CaSiO3） fibers. Composites made by mixing their powder precursors with deionized water at room temperature, were investigated for their composition using X-ray diffraction （XRD） and Thermogravimetric Analysis （TGA）, for their microstructure using Scanning Electron microscopy （SEm）, for their compressive strengths and modulus of elasticity, and for setting time measurements. In addition, cement composites were evaluated for their preliminary bioactivity in a protein-free Simulated Body Fluid （SBF） for up to 14 days. Results show the improvement of mechanical properties and bioactivity of the composites using acid-treated wollastonite fibers. This was attributed to the formation of hydrated silica layer on the surface of the acid-treated fibers which improved the binding with the gypsum matrix and provided nucleating sites for the deposition of bone-like apatite spherolites from SBF media.

关键词： gypsum wollastonite bone cement biomimetic SBF microstructure

Improved multileader Optimization with Shadow Encryption for medical Images in IoT Environment

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Computers, materials & Continua 2023年第2期74卷 3133-3149页

作者： mesfer Al Duhayyim mohammed maray Ayman Qahmash Fatma S.Alrayes nuha Alshuqayran Jaber S.Alzahrani mohammed Alghamdi Abdullah mohamed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information and Technology Systems College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data *** healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care *** general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty *** the same time,it is also significant to maintain the delicate contents of health care images during reconstruction ***,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive *** current study introduces Improved multileader Optimization with Shadow Image Encryption for medical Image Security(ImLOSIE-mIS)technique for IoT *** aim of the proposed ImLOSIE-mIS model is to accomplish security by generating shadows and encrypting them *** do so,the presented ImLOSIE-mIS model initially generates a set of shadows for every input medical ***,shadow image encryption process takes place with the help of multileader Optimization(mLO)withHomomorphic Encryption(ImLO-HE)technique,where the optimal keys are generated with the help of mLO *** the receiver side,decryption process is initially carried out and shadow image reconstruction process is *** experimentation analysis was carried out on medical images and the results inferred that the proposed ImLOSIE-mIS model is an excellent performer compared to other *** comparison study outcomes demonstrate that ImLOSIE-mIS model is robust and offers high security in IoT-enabled healthcare environment.

关键词： medical image security image encryption shadow images homomorphic encryption optimal key generation

Optimal Fuzzy Logic Enabled Intrusion Detection for Secure IoT-Cloud Environment

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Computers, materials & Continua 2023年第3期74卷 6737-6753页

作者： Fatma S.Alrayes nuha Alshuqayran mohamed K Nour mesfer Al Duhayyim Abdullah mohamed Amgad Atta Abdelmageed mohammed Gouse Pasha mohammed Ishfaq Yaseen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Recently,Internet of Things(IoT)devices have developed at a faster rate and utilization of devices gets considerably increased in day to day *** the benefits of IoT devices,security issues remain challenging owing to the fact that most devices do not include memory and computing resources essential for satisfactory security ***,IoT devices are vulnerable to different kinds of attacks.A single attack on networking system/device could result in considerable data to data security and *** the emergence of artificial intelligence(AI)techniques can be exploited for attack detection and classification in the IoT *** this view,this paper presents novel metaheuristics feature selection with fuzzy logic enabled intrusion detection system(mFSFL-IDS)in the IoT *** presented mFSFL-IDS approach purposes for recognizing the existence of intrusions and accomplish security in the IoT *** achieve this,the mFSFL-IDS model employs data pre-processing to transform the data into useful ***,henry gas solubility optimization(HGSO)algorithm is applied as a feature selection approach to derive useful feature ***,adaptive neuro fuzzy inference system(ANFIS)technique was utilized for the recognition and classification of intrusions in the ***,binary bat algorithm(BBA)is exploited for adjusting parameters involved in the ANFIS model.A comprehensive experimental validation of the mFSFL-IDS model is carried out using benchmark dataset and the outcomes are assessed under distinct *** experimentation outcomes highlighted the superior performance of the mFSFL-IDS model over recentapproaches with maximum accuracy of 99.80%.

关键词： Cloud computing security fuzzy logic intrusion detection internet of things metaheuristics

Hot-pressed graphene nanoplatelets or/and zirconia reinforced hybrid alumina nanocomposites with improved toughness and mechanical characteristics

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Journal of materials Science & Technology 2020年第5期40卷 135-145页

作者： Iftikhar Ahmad mohammad Islam nuha Al Habis Shahid Parvez Center of Excellence for Research in Engineering materials Deanship of Scientific ResearchKing Saud UniversityP.O.Box 800Riyadh 11421Saudi Arabia mechanical Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh 11421Saudi Arabia

This work explains the synergistic contribution of graphene nanoplatelets(GNP)and zirconia ceramic nanoparticles(ZrO2)on the microstructure,mechanical performance and ballistic properties of the alumina(Al2O3)ceramic hybrid *** the benchmarked monolithic alumina,the hotpressed hybrid nanocomposite microstructure demonstrated 68%lower grain size due to grain pinning phenomenon by the homogenously distributed reinforcing GNP(0.5 wt%)and zirconia(4 wt%)***,the hybrid nanocomposite manifested 155%better fracture toughness(KIC)and 17%higher microhardness as well as 88%superior ballistic trait over the monolithic alumina,*** superior mechanical and ballistic performance of the hybrid nanocomposites was attributed to the combined role of zirconia nanoparticles and GNP nanomaterial in refining the microstructure and inducing idiosyncratic strengthening/toughening *** combined electron microscopy revealed complicated physical interlocking of the GNP into the microstructure as well as excellent bonding of the GNP with alumina at their interface in the hybrid *** also probed the efficiency of the pull-out and crack-bridging toughening mechanisms through proven quantitative *** on the information extracted from the in-depth SEm/TEm investigation,we outlined schematic models for understating the reinforcing ability as well as toughening mechanisms in the hybrid nanocomposites and meticulously *** hot-pressed hybrid nanocomposites owning high toughness and hardness may have applications in advanced armor technology.

关键词： Graphene Alumina Zirconia Toughness Hybrid nanocomposites

Functionality of Covalent Organic Framework (COF) in Gas Storage Application: First Principal Study

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Computational Chemistry 2023年第3期11卷 53-66页

作者： mashael Alharbi Raghad Aljohani Raghad Alzahrani Yara Alsufyani nuha Alsmani Faculty of Science Chemistry Department King Abdulaziz University Jeddah Saudi Arabia

Industrial growth in recent years led to air pollution and an increase in concentration of hazardous gases such as O3 and NO. Developing new materials is important to detect and reduce air pollutants. While catalytic decomposition and zeolites are traditional ways used to reduce the amount of these gases. We need to develop and explore new promising materials. Covalent organic framework (COF) has become an attractive platform for researcher due to its extended robust covalent bonds, porosity, and crystallinity. In this study, first principal calculations were performed for gases adsorption using COFs containing nitrogen and π-bonds. Different building blocks (BBs) and linkers (LINKs/LINK1 & LINK2) were investigated by means of density functional theory (DFT) calculations with B3LYP and 3-21G basis sets to calculate the binding energies of gases @COF systems. Electrostatic potential maps (ESPm), mulliken charges and non-covalent interaction (NCI) are used to understand the type of interactions between gas and COFs fragments. O3 was found to bind strongly with COF system in comparison with NO which could make COF a useful selective material for mixed gases environment for sensing and removal application.

关键词： Covalent Organic Framework (COF) Ozonestorage Nitric Oxide Storage First Principal Study Binding Energies Non-Covalent Interaction (NCI) Analysis Effect of π-Linkers and Building Blocks