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Engineering（科研） 2011年第3期3卷 215-226页

作者： Ayman G. Awadallah mohamed elgamal Ashraf ElMostafa Hesham ElBadry 不详

The availability of data is an important aspect in frequency analysis. This paper explores the joint use of lim- ited data from ground rainfall stations and TRMM data to develop Intensity Duration Frequency (IDF) curves, where very limited ground station rainfall records are available. Homogeneity of the means and variances are first checked for both types of data. The study zone is assumed to be belonging to the same region and checked using the Wiltshire test. An Index Flood procedure is adopted to generate the theoretical regional distribution equation. Rainfall depths at various return periods are calculated for all stations and plotted spatially. Regional patterns are identified and discussed. TRMM data are used to develop ratios between 24-hr rainfall depth and shorter duration depths. The regional patterns along with the developed ratios are used to develop regional IDF curves. The methodology is applied on a region in the North-West of Angola.

关键词： Rainfall Frequency Analysis Regional Analysis Intensity Duration Frequency TRMM Angola

Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

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Computer Systems Science & Engineering 2023年第3期44卷 1869-1880页

作者： S.Siamala Devi K.Venkatachalam Yunyoung Nam mohamed Abouhawwash Department of Computer Science and Engineering Sri Krishna College of TechnologyCoimbatore641042India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies.Early diagnosis of many diseases will improve the patient life.The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things(IoT),Wireless Sensor Networks(WSN),Embedded systems,Deep learning approaches and Optimization and aggregation methods.The data generated through these technologies will demand the bandwidth,data rate,latency of the network.In this proposed work,efficient discrete grey wolf optimization(DGWO)based data aggregation scheme using Elliptic curve elgamal with Message Authentication code(ECEMAC)has been used to aggregate the parameters generated from the wearable sensor devices of the patient.The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO.Aggregation scheme will reduce the number of transmissions over the network.The aggregated data are preprocessed at edge node to remove the noise for better diagnosis.Edge node will reduce the overhead of cloud server.The aggregated data are forward to cloud server for central storage and diagnosis.This proposed smart diagnosis will reduce the transmission cost through aggrega-tion scheme which will reduce the energy of the system.Energy cost for proposed system for 300 nodes is 0.34μJ.Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme(SPPDA),concealed data aggregation scheme for multiple application(CDAMA)and secure aggregation scheme(ASAS)are 1.3μJ,0.81μJ and 0.51μJ respectively.The optimization approaches and encryption method will ensure the data privacy.

关键词： Discrete grey wolf optimization data aggregation cloud computing IoT WSN smart healthcare elliptic curve elgamal energy optimization

Deep Learning Enabled Disease Diagnosis for Secure Internet of Medical Things

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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 domain.Since 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 data.Privacy and security of the data,gathered by IoMT gadgets,are major issues while transmitting or saving it in cloud.The advancements made in Artificial Intelligence(AI)and encryption techniques find a way to handle massive quantities of medical data and achieve security.In this view,the current study presents a new Optimal Privacy Preserving and Deep Learning(DL)-based Disease Diagnosis(OPPDL-DD)in IoMT environment.Initially,the proposed model enables IoMT devices to collect patient data which is then preprocessed to optimize quality.In order to decrease the computational difficulty during diagnosis,Radix Tree structure is employed.In addition,elgamal public key cryptosystem with Rat Swarm Optimizer(EIG-RSO)is applied to encrypt the data.Upon the transmission of encrypted data to cloud,respective decryption process occurs and the actual data gets reconstructed.Finally,a hybridized methodology combining Gated Recurrent Unit(GRU)with Convolution Neural Network(CNN)is exploited as a classification model to diagnose the disease.Extensive sets of simulations were conducted to highlight the performance of the proposed model on benchmark dataset.The 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

Review on the Estimating the Effective Way for Managing the Produced Water: Case Study

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Open Journal of Modern Hydrology 2021年第2期11卷 19-37页

作者： mohamed A. Kassab Ali E. Abbas Iman elgamal Basem M. Shawky Mahmoud F. Mubarak R. Hosny Egyptian Petroleum Research Institute (EPRI) Cairo Egypt Faculty of Petroleum and Mining Engineering-Suez University Suez Egypt Bader EL-Din Petroleum Company (BAPETCO) Cairo Egypt

Water manufactured is the primary waste source in the oil and gas industry. Because of the rising amount of waste worldwide, the environmental effect of wastewater has become a primary environmental concern in recent years. The vast amounts involved have resulted in considerable costs to the industry for handling produced water. This research explains the wide variety of choices for water management. This research’s first phase was water minimization techniques, consisting of three different applications made in three different wells (Well 1, Well 2 and Well 3) and water recycling and reuse by two techniques. In Well 1, Mechanical shut-off technique was applied using through tubing bridge plug and 5 m cement dumped above it to isolate the watered out zone;as per water oil ration plot the water cut is decreased from 100% to 4% and the production is increased from 0 to 400 bcpd. In Well 2, Chemical shut-off technique using a polymer called Brightwater has been used to block channeling through high permeability intervals after PLT log detected it, and the result was brilliant, the water cut decreased from 60% to 25%, also the oil production increase from 500 to 3000 bopd. In Well 3, downhole separator installed in it using workover (unfortunately, this technique is not applied in middle east till the moment so this application is taken from an oil field in Canada)and the result was perfect, the water cut decreased from 70% to 28%, also the oil production increase from 44 to 100 bopd. This study tried to clarify and compare the most widely used water management techniques using one of the Western Desert (W.D.) (enhanced for oil recovery, constructed wetland).

关键词： Produced Water Water Production Problem Management Techniques Water Minimization Techniques Recycling and Reusing Technologies