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Deep Learning Enabled Disease Diagnosis for Secure Internet of Medical Things

Computers, Materials & Continua 2022年第10期73卷 965-979页

作者： Sultan Ahmad Shakir Khan mohamed fahad Al.Ajmi Ashit Kumar Dutta L.Minh Dang Gyanendra Prasad Joshi Hyeonjoon Moon Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia College of Pharmacy King Saud UniversityRiyadh11451Saudi Arabia Department of Computer Science and Information System College of Applied SciencesAlMaarefa UniversityRiyadh11597Saudi Arabia Department of Information Technology FPT UniversityHo Chi Minh CityVietnam Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In recent times,Internet of Medical Things(IoMT)gained much attention in medical services and healthcare management *** healthcare sector generates massive volumes of data like personal details,historical medical data,hospitalization records,and discharging records,IoMT devices too evolved with potentials to handle such high quantities of *** and security of the data,gathered by IoMT gadgets,are major issues while transmitting or saving it in *** advancements made in Artificial Intelligence(AI)and encryption techniques find a way to handle massive quantities of medical data and achieve *** this view,the current study presents a new Optimal Privacy Preserving and Deep Learning(DL)-based Disease Diagnosis(OPPDL-DD)in IoMT ***,the proposed model enables IoMT devices to collect patient data which is then preprocessed to optimize *** order to decrease the computational difficulty during diagnosis,Radix Tree structure is *** addition,ElGamal public key cryptosystem with Rat Swarm Optimizer(EIG-RSO)is applied to encrypt the *** the transmission of encrypted data to cloud,respective decryption process occurs and the actual data gets ***,a hybridized methodology combining Gated Recurrent Unit(GRU)with Convolution Neural Network(CNN)is exploited as a classification model to diagnose the *** sets of simulations were conducted to highlight the performance of the proposed model on benchmark *** experimental outcomes ensure that the proposed model is superior to existing methods under different measures.

关键词： Internet of medical things privacy security encryption radix tree deep learning

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Chromatographic finger print analysis of anti-inflammatory active extract fractions of aerial parts of Tribulus terrestris by HPTLC technique

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Asian Pacific Journal of Tropical Biomedicine 2014年第3期4卷 203-208页

作者： Mona Salih Mohammed mohamed fahad Alajmi Perwez Alam Hassan Subki Khalid Abelkhalig Muddathir Mahmoud Wadah Jamal Ahmed Department of Pharmacognosy Faculty of PharmacyUniversity of KhartoumSudan Department of Pharmacognosy College of PharmacyKing Saud UniversityRiyadh-11451P.O.Box.2457Kingdom of Saudi Arabia Medicinal and Aromatic Plants Research Institute National Council for ResearchKhartoumSudan

Objective:To develop HPTLC fingerprint profile of anti-inflammatory active extract fractions of Tribulus terrestris(family Zygophyllaceae).Methods:The anti-inflammatory activity was tested for the methanol and its fractions(chloroform,ethyl acetate,n-butanol and aqueous)and chloroform extract of Tribulus terrestris(aerial parts)by injecting different groups of rats(6 each)with carrageenan in hind paw and measuring the edema volume before and 1,2 and 3 h after carrageenan *** group received saline *** extracts treatment was injected *** doses of 200 mg/kg 1 h before carrageenan ***(30 mg/kg)was used as *** studies were carried out using CAMAG HPTLC system equipped with Linomat IV *** scanner *** 3,CAMAG ADC 2 and WIN CATS-4 software for the active fractions of chloroform fraction of methanol ***:The methanol extract showed good antiedematous effect with percentage of inhibition more than 72%,indicating its ability to inhibit the inflammatory *** methanol extract was re-dissolved in 100 mL of distilled water and fractionated with chloroform,ethyl acetate and *** four fractions(chloroform,ethyl acetate,n-butanol and aqueous)were subjected to anti-inflammatory *** fraction showed good anti-inflammatory activity at dose of 200 mg/*** fraction was then subjected to normal phase silica gel column chromatography and eluted with petroleum ether-chloroform,chloroform-ethyl acetate mixtures of increasing polarity which produced 15 fractions(F1-F15).Only fractions F1,F2,F4,F5,F7,F9,F11 and F14 were found to be active,hence these were analyzed with HPTLC to develop their finger print *** fractions showed different spots with different R_f ***:The different chloroform fractions F1,F2,F4,F5,F7,F9,F11 and F14 revealed 4,7,7,8,9,7,7 and 6 major spots,*** results obtained in this experiment strongly support and vali

关键词： Tribulus terrestris Finger print Anti-inflammatory Standardization HPTLC

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Artificial Intelligence Prediction of One-Part Geopolymer Compressive Strength for Sustainable Concrete

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 525-543页

作者： mohamed Abdel-Mongy Mudassir Iqbal M.Farag Ahmed.M.Yosri fahad Alsharari Saif Eldeen A.S.Yousef Department of Civil Engineering College of EngineeringJouf UniversitySakaka72388Saudi Arabia Department of Civil Engineering University of Engineering and TechnologyPeshawar54890Pakistan Civil Engineering Department Faculty of EngineeringAl-Azhar UniversityCairo11884Egypt Civil Engineering Department Faculty of EngineeringAswan UniversityAswan81528Egypt

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological *** terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part ***,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely ***,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part *** database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing *** performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed *** and parametric analysis were also performed to identify the significant contributor to *** to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 *** water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

关键词： Artificial intelligence techniques one-part geopolymer artificial neural network gene expression modelling sustainable construction polymers

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Assessment of Exposure Due to Technologically Enhanced Natural Radioactivity in Various Samples of Moroccan Building Materials

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World Journal of Nuclear Science and Technology 2018年第4期8卷 176-189页

作者： Bouchaib Kassi Aziz Boukhair Khadija Azkour mohamed fahad Mohammed Benjelloun Abdel-Mjid Nourreddine Laboratory of Physics and Nuclear Techniques Atomic and Molecular Chouaib Doukkali University El Jadida Morocco Regional Center of the Trades of Education and Training El Jadida Morocco Ministère de l’Intérieur El Jadida Morocco Groupe RaMsEs Institut Pluridisciplinaire Hubert Curien (IPHC) Université de Strasbourg Strasbourg France

The aim of our present work is to measure the specific activities of the radionuclides 226Ra, 232Th, 40K and the exhalation rates in terms of area and mass of 222Rn in some samples of building materials commonly used in Morocco in order to evaluate the radiological risk caused by natural radioactivity. To this end, the analyses were carried out, using two nuclear techniques, namely high resolution gamma spectrometry and alpha dosimetry based on the use of LR115, on 50 samples collected from large commercial suppliers in Morocco. The results of these analyses show that the average specific activities of 226Ra, 232Th and 40K in these materials vary from 9 to 52 Bq/kg, 3 to 63 Bq/kg and 68 to 705 Bq/kg respectively. These activities remain within the permissible limits of 35 Bq/kg, 30 Bq/kg and 370 Bq/kg respectively, with the exception of a few samples of red brick, gray cement, ceramic and granite. The activity of the radium equivalent (Raeq), the internal (Hin) and external (Hex) hazard indices, the absorbed dose rate, the total annual effective dose , the excess lifetime cancer risk (ELCR) as well as volumic activities, exhalation rates in terms of area (ES) and mass (EM) are calculated for the samples analyzed in this work in order to assess the radiological risks resulting from the use of these materials in various construction activities. It seems that the values of these indices vary from 19 to 196 Bq/kg, 0.08 to 0.67, 0.05 to 0.53, 9 to 91 nGy/h, 0.05 to 0.56 mSv/y, 0.19 × 10−3 to 1.96 × 10−3, 72 to 350 Bq/m3, 56 to 273 mBq⋅m−2⋅h−1 and 3 to 15 mBq⋅kg−1⋅h−1 respectively. The lowest values are identified for gypsum, while the highest are attributed to granite. All of the obtained results of these indices respect the permissible limits except for the Raeq in some granite samples, the ELCR index in all samples except gypsum and the radon volumic activity in some gray cement samples, ceramic and granite. As a

关键词： Building Materials Natural Radioactivity Radionuclide Radon Exhalation Rate Radium Equivalent Annual Effective Dose

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Numerical Modeling and Technico-Economic Analysis of a Hybrid Energy Production System for Self-Consumption: Case of Rural Area in the Comoros

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Journal of Power and Energy Engineering 2024年第5期12卷 24-59页

作者： fahad Maoulida mohamed Aboudou Kassim Rabah Djedjig Ahmed Ihlal Mohammed El Ganaoui LERMAB Laboratory of Studies and Research on Wood Material IUT of Longwy University of Lorraine Cosnes-et-Romain Longwy France LEMA Energy and Applied Mechanics Laboratory Faculty of Sciences and Techniques University of Comoros Moroni Comoros IREMIS Institute University of Mayotte Mayotte France LMER Laboratory of Materials and Renewable Faculty of Sciences University Ibn Zohr BP Agadir Morocco

This study aims to provide electricity to a remote village in the Union of Comoros that has been affected by energy problems for over 40 years. The study uses a 50 kW diesel generator, a 10 kW wind turbine, 1500 kW photovoltaic solar panels, a converter, and storage batteries as the proposed sources. The main objective of this study is to conduct a detailed analysis and optimization of a hybrid diesel and renewable energy system to meet the electricity demand of a remote area village of 800 to 1500 inhabitants located in the north of Ngazidja Island in Comoros. The study uses the Hybrid Optimization Model for Electric Renewable (HOMER) Pro to conduct simulations and optimize the analysis using meteorological data from Comoros. The results show that hybrid combination is more profitable in terms of margin on economic cost with a less expensive investment. With a diesel cost of $1/L, an average wind speed of 5.09 m/s and a solar irradiation value of 6.14 kWh/m2/day, the system works well with a proportion of renewable energy production of 99.44% with an emission quantity of 1311.407 kg/year. 99.2% of the production comes from renewable sources with an estimated energy surplus of 2,125,344 kWh/year with the cost of electricity (COE) estimated at $0.18/kWh, presenting a cost-effective alternative compared to current market rates. These results present better optimization of the used hybrid energy system, satisfying energy demand and reducing the environmental impact.

关键词： Hybrid System Rural Area Electrification Comoros Techno-Economic Analysis PV-Wind-Diesel-Battery Meteorological Data HOMER Energy Pro

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Use of Topical Complementary and Alternative Medicines (CAM) in Diabetic Septic Foot Disease in Makkah Region, Western of Saudi Arabia, an Exploratory Study

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Journal of Biosciences and Medicines 2024年第3期12卷 245-258页

作者： mohamed Elamin Salih Hatim Alrizqi Mohammed Hussain Abdullah Alshumrani Ismail Alhasani Ali Alkhamisi Hamzah Alsayed fahad Alqarni Department of Surgery Faculty of Medicine University of Umm AlQura Mecca Saudi Arabia Faculty of Medicine University of Umm AlQura Mecca Saudi Arabia

Diabetes is a chronic condition that is significantly impacted daily by environment. At least one in five Saudis, suffer from diabetes. “Diabetes is a pandemic of unprecedented magnitude spiraling out of control” (Boulton). Saudi Arabia ranks the second highest in the Middle East, and is the seventh in the world for the prevalence of diabetes (WHO). Diabetes mellitus (DM) has been found to be related to high mortality, morbidity accompanied by poor general health and lower quality of life. Current Saudi diabetes patients’ behaviors, practices, and beliefs regarding foot health problems such as ulcers, are not well investigated. Diabetic patients frequently utilize natural remedies and Herbs for self-medication as a part of complementary and alternative Medicine. Aim of study: To explore the widespread use of the alternative remedies in the local communities of the Western Saudi Arabia, the drives behind using and to focus on the potential adverse effects following their usage. Method: A descriptive, cross-sectional study of 386 diabetic patients with feet problems in Makkah Region, West of Saudi Arabia during the period April - June 2023. Results: Out of the 531 participants, only 386 participants reported diabetic foot disorder (DFD). Most of the participant were above 65 years of age group (24.61 %). Male (52.08%) more than female (47.92%) in the research group. All of the participants had diabetic foot disorders at least once. The prevalence of complementary and alternative medicines (CAM) use among them was 67.88%, as solitary or in combination with hospital medicines. Honey headed the list followed by myrrh and black seeds. Acquaintances advice (59.54%) was the most reason for using the alternative medicine. 60.30% of Diabetic foot patient complained of adverse effects during CAM remedies use. Conclusion: Consumption of CAM remedies among diabetic patients for Diabetic Foot Disorder (DFD) is common. Honey headed the list followed by myrrh and black seeds. Addit

关键词： Diabetic Foot Ulcer Diabetes Complementary and Alternative Medicine CAM West of Saudi Arabia

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Feasibility Study for a Hybrid Power Plant(PV-Wind-Diesel-Storage)Connected to the Electricity Grid

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Fluid Dynamics & Materials Processing 2022年第6期18卷 1607-1617页

作者： fahad Maoulida Kassim mohamed Aboudou Djedjig Rabah Mohammed El-Ganaoui Laboratory LEMAFaculty of Sciences and TechniquesUniversity of ComorosMoroniComoros Laboratory LERMABIUT Henri Poincaréof LongwyUniversity of LorraineNancyFrance IREMIS Institute CUFRUniversity of MayotteDembeni MayotteFrance

In this work,we present a feasibility study for a new hybrid power plant(PV-Wind-Diesel-Storage)directly connected to the electrical *** simulations are performed to verify the performance of the hybrid system under different scenarios using real meteorological *** is shown that the performances of the hybrid system connected to the electrical network depend obviously on the available energy resources and constraints because the renewable energies are *** addition,the price of the kWh of electricity supplied by the hybrid system is determined,which amounts to$0.209/kWh,which is very cost effective and satisfactory for the considered sample conditions(Comoros Island).

关键词： Hybrid energy renewable energy HOMER connected grid

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Lean HC gas injection pilots analysis and IPR back calculation to examine the impact of asphaltene deposition on flow performance

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Petroleum Research 2019年第1期4卷 84-95页

作者： fahad I.Syed mohamed Boukhatem Ahmed A.Al Kiyoumi Abu Dhabi National Oil Company(ADNOC)Offshore Abu DhabiUnited Arab Emirates

Gas injection is one of the most economical and effective approach to improve oil ***,outcome of such approach is contingent to reservoir heterogeneities impacting gas override and ***,injected fluid composition and its compatibility with the reservoir fluid potentially impact flow assurance issues such as asphaltene precipitation into the wellbore and surface *** objective of this paper is to examine the lesson learnt from a couple of field scale 5 spot patterned lean hydrocarbon gas injection pilots which were deployed in a heterogeneous carbonate formation of a giant field located offshore Abu Dhabi under secondary and tertiary drive *** pilots provides a valuable insight on production performance,pressure support,gravity override,fluid composition and evidence of asphaltene deposition that resulted in heavy production loss prior to the solvent *** paper presents the overall pilot performance including pattern recovery,fluid front movement,potential role of heterogeneity in gas breakthrough timings and the operational events to witness asphaltene deposition affecting the flow *** deposited asphaltene cake thickness was measured mechanically during routine tubing clearance check operation that was helpful in estimating production loss due to altered production tubing flow *** an integrated approach is applied to confirm the AOP laboratory measurements with the actual deposits of asphaltene that were found in to the production *** order to confirm the effect of asphaltene deposition on inflow from near wellbore formation to the wellbore,a straightforward yet innovative nodal analysis approach was applied to study well performance using the calibrated and history matched well *** was noticed that not only the outflow was altered because of asphaltene deposition into wellbore but also the inflow(productivity index)was seriously impacted potentially due to asphaltene depos

关键词： Gas injection Well performance Asphaltene deposition Formation damage

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Machine Learning-Based Channel State Estimators for 5G Wireless Communication Systems

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工程与科学中的计算机建模（英文） 2023年第4期135卷 755-778页

作者： mohamed Hassan Essai Ali fahad Alraddady Mo’ath Y.Al-Thunaibat Shaima Elnazer Department of Electrical Engineering Faculty of EngineeringAl-Azhar UniversityQena83513Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Management Information Systems Taif UniversityTaif21944Saudi Arabia

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state ***,it utilizes pilots to offer more helpful information about the communication *** proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based *** CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based *** three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based *** BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)*** addition,the computational and learning time complexities for DNN-CSEs are *** estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

关键词： DLNNs channel state estimator 5G and beyond communication systems robust loss functions

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Hybrid Smart Contracts for Securing IoMT Data

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Computer Systems Science & Engineering 2023年第1期44卷 457-469页

作者： D.Palanikkumar Adel fahad Alrasheedi P.Parthasarathi S.S.Askar mohamed Abouhawwash Department of Computer Science and Engineering Dr NGP Institute of TechnologyCoimbatore641048India Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia Department of Computer Science and Engineering Bannari Amman Institute of TechnologySathy638401India Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Data management becomes essential component of patient *** of Medical Things(IoMT)performs a wireless communication between E-medical applications and human *** of consulting a doctor in the hospital,patients get health related information remotely from the *** main issues in the E-Medical application are lack of safety,security and priv-acy preservation of patient’s health care *** overcome these issues,this work proposes block chain based IoMT Processed with Hybrid consensus protocol for secured *** health data is collected from physician,smart devices *** main goal is to store this highly valuable health related data in a secure,safety,easy access and less cost-effective *** this research we combine two smart contracts such as Practical Byzantine Fault Tolerance with proof of work(PBFT-PoW).The implementation is done using cloud technology setup with smart contracts(PBFT-PoW).The accuracy rate of PBFT is 90.15%,for PoW is 92.75%and our proposed work PBFT-PoW is 99.88%.

关键词： PoW byzantine fault tolerance IoMT cloud computing health care data

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