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Thermodynamic Analysis and Optimization of Flat Plate Solar Collector Using TiO/Water Nanofluid

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Journal of Harbin Institute of Technology(New series) 2023年

作者： Firas F.Qader falah z.mohammed Barhm Mohamad Technical Engineering College-Kirkuk Northern Technical University Department of Petroleum Technology Koya Technical Institute Erbil Polytechnic University Medical Device Technology Engineering AL-Qalam University College

To research solar energy’s efficiency and environmental benefits， the thermal efficiency， exergy， and entropy of solar collectors were calculated. The experiment involved two glass-topped collectors， fluid transfer tubes， and aluminum heat-absorbing plates. Glass wool insulation minimized heat loss. A 0.5% TiO2/Water nanofluid was created using a mechanical and ultrasonic stirrer. Results showed that solar radiation increased thermal efficiency until midday， reaching 48.48% for water and 51.23% for the nanofluid. With increasing mass flow rates from 0.0045 kg/s to 0.02 kg/s， thermal efficiency improved from 16.26% to 47.37% for water and from 20.65% to 48.76% for the nanofluid. Filtered water provided 380 W and 395 W of energy in March and April， while the nanofluid increased it to 395 W and 415 W during these months. Mass flow generated energy， and the Reynolds number raised entropy. The noon exergy efficiency for nanofluids was 50%-55%， compared to 30% for water. At noon， the broken exergy measured 877.53 W for the nanofluid and 880.12 W for water. In Kirkuk， Iraq， the 0.5% TiO2/Water nanofluid outperformed water in solar collectors.

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Exploring dielectric phenomena in sulflower-like nanostructures via Monte Carlo technique

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Communications in Theoretical Physics 2024年第4期76卷 188-198页

作者： N Saber z Fadil Hussein Sabbah A Mhirech B Kabouchi L Bahmad Chaitany Jayprakash Raorane Siva Sankar Sana Hassan Fouad Mohamed Hashem Laboratory of Condensed Matter and Interdisciplinary Sciences(LaMCScI) Research Unit Labelled CNRSTURL-CNRST-17.Faculty of SciencesPO Box 1014Mohammed Ⅴ University in RabatMorocco College of Engineering and Technology American University of the Middle EastEgaila 54200Kuwait School of Chemical Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Applied Medical Science Department Community CollegeKing Saud UniversityPO Box 11433Riyadh Saudi Arabia Department of Dental Health College of Applied Medical SciencesKing Saud UniversityPO Box 12372RiyadhSaudi Arabia

This research focuses on the electric behavior of a mixed ferrielectric sulflower-like *** structure includes a core with spin S_(i)^(z)-1 atoms and a shell with spin σ_(j)^(z)-5/2 *** Blume–Capel model and the Monte Carlo technique(MCt)with the Metropolis algorithm are *** are established for absolute zero,investigating stable spin configurations correlated with various physical *** MCt method explores phase transition behavior and electric hysteresis cycles under different physical parameters.

关键词： sulfower-like nanostructure dielectric characteristics Monte Carlo technique phase transition phase diagrams electric hysteresis

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Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

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Computers, Materials & Continua 2022年第5期71卷 2459-2476页

作者： Sonali Dash Sahil Verma Kavita N.z.Jhanjhi Mehedi Masud mohammed Baz Department of Electronics and Communication Engineering Raghu Institute of Technology(A)Visakhapatnam531162India Department of Computer Science and Engineering Chandigarh UniversityMohali140413India School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21994Saudi Arabia

Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye *** diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular *** various approaches for retinal vessel segmentation are extensively utilized,however,the responses are lower at vessel’s *** curvelet transform signifies edges better than wavelets,and hence convenient for multiscale edge *** bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong *** bilateral filter is an advanced version of bilateral filter that regulates the contrast while preserving the ***,in this paper a fusion algorithm is recommended by fusing fast bilateral filter that can effectively preserve the edge details and curvelet transform that has better capability to detect the edge direction feature and better investigation and tracking of significant characteristics of the *** C mean thresholding is used for the extraction of *** recommended fusion approach is assessed on DRIVE *** results illustrate that the fusion algorithm preserved the advantages of the both and provides better *** results demonstrate that the recommended method outperforms the traditional approaches.

关键词： Blood vessel extraction curvelet transform fast bilateral filter C mean thresholding

Multi-Scale Network for Thoracic Organs Segmentation

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Computers, Materials & Continua 2022年第2期70卷 3251-3265页

作者： Muhammad Ibrahim Khalil Samabia Tehsin Mamoona Humayun N.z Jhanjhi mohammed A.Alzain Department of Computer Science Bahria UniversityIslamabadPakistan Department of Information systems College of Computer and Information SciencesJouf UniversityKSA School of Computer Science and Engineering(SCE) Taylor’s UniversityMalaysia Center for Smart Society 5.0(CSS5) Faculty of Innovation and Technology(FIT)Taylor’s UniversityMalaysia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Medical Imaging Segmentation is an essential technique for modern medical *** is the foundation of many aspects of clinical diagnosis,oncology,and computer-integrated surgical *** significant successes have been achieved in the segmentation of medical images,DL(deep learning)*** delineation of OARs(organs at risk)is vastly dominant but it is prone to errors given the complex irregularities in shape,low texture diversity between tissues and adjacent blood area,patientwide location of organisms,and weak soft tissue contrast across adjacent organs in CT *** now several models have been implemented onmulti organs segmentation but not caters to the problemof imbalanced classes some organs have relatively small pixels as compared to *** segment OARs in thoracic CT images,we proposed the model based on the encoder-decoder approach using transfer learning with the efficientnetB7 DL *** have built a fully connected CNN(Convolutional Neural network)having 5 layers of encoding and 5 layers of decoding with efficientnetB7 specifically to tackle imbalance class pixels in an accurate way for the segmentation of *** methodology achieves 0.93405 IOU score,0.95138 F1 score and class-wise dice score for esophagus 0.92466,trachea 0.94257,heart 0.95038,aorta 0.9351 and background *** results showed that our proposed framework can be segmented organs accurately.

关键词： Deep learning convolutional neural network computed tomography organs at risk computer-aided diagnostic

Hybrid GrabCut Hidden Markov Model for Segmentation

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Computers, Materials & Continua 2022年第7期72卷 851-869页

作者： Soobia Saeed Afnizanfaizal Abdullah N.z.Jhanjhi Mehmood Naqvi Mehedi Masud mohammed A.Alzain Department of Software Engineering UniversitiTeknologi Malaysia-UTM81310Malaysia School of Computer Science and Engineering SCE Taylor’s UniversitySubang Jaya47500Malaysia Department of Engineering and Technology Mohak CollegeAlbertaCanada Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Diagnosing data or object detection in medical images is one of the important parts of image segmentation especially those data which is less effective to identify inMRI such as low-grade tumors or cerebral spinal fluid(CSF)leaks in the *** aim of the study is to address the problems associated with detecting the low-grade tumor and CSF in brain is difficult in magnetic resonance imaging(MRI)images and another problem also relates to efficiency and less execution time for segmentation of medical *** tumor and CSF segmentation using trained light field database(LFD)datasets of MRI *** research proposed the new framework of the hybrid k-Nearest Neighbors(k-NN)model that is a combination of hybridization of Graph Cut and Support Vector Machine(GCSVM)and Hidden Markov Model of k-Mean Clustering Algorithm(HMMkC).There are four different methods are used in this research namely(1)SVM,(2)GrabCut segmentation,(3)HMM,and(4)k-mean clustering *** this framework,on the one hand,phase one is to perform the classification of SVM and Graph Cut algorithm to create the maximum margin *** research use GrabCut segmentation method which is the application of the graph cut algorithm and extract the data with the help of scaleinvariant features *** the other hand,in phase two,segment the low-grade tumors and CSF using a method adapted for HMkC and extract the information of tumor or CSF fluid by GCHMkC including iterative conditional maximizing mode(ICMM)with identifying the range of *** evaluation is also performing by the comparison of existing techniques in this *** conclusion,our proposed model gives better results than *** proposed model helps to common man and doctor that can identify their condition of brain *** future,this will model will use for other brain related diseases.

关键词： SVM tumor CSF k-NN MRI grabcut segmentation HMM

Preliminary Palynostratigraphic Data on the Middle Albian-Lower Cenomanian of the Tarfaya Basin, Southwest Morocco

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Open Journal of Geology 2024年第4期14卷 548-568页

作者： Khaoula Chafai Touria Hssaida Wafaa Maatouf Mohamed z. Yousfi Sara Chakir Soukaina Jaydawi Hanane Khaffou Department of Geology Faculty of Sciences Ben M&#8217Sik University Hassan II Casablanca Morocco Department of Petroleum Laboratory Office National des Hydrocarbures et des Mines Rabat Morocco Department of Geology Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fes Morocco Department of Geology Faculty of Sciences Mohammed V University Rabat Morocco

The Tarfaya-Laayoune-Boujdour basin is of great interest to oil exploration;on this aspect, there has been exploration by the Moroccan National Office of Hydrocarbons and Mining, which has shown indices of oil and/or gas recorded in most wells drilled in the Moroccan Atlantic margin. FD-1 well, object of this study, is one of these wells located in the offshore Tarfaya-Laayoune-Boujdour basin. A palynological examination of the processed samples revealed the existence of organic palynomorphs, well conserved and rich in dinoflagellate cysts. The latter are composed of worldwide marker taxa of high stratigraphic resolutions. Thus, the middle upper Albian (3408 - 3408.5 m) is determined by the presence of Cribroperidinium tensiftense, Tehamadinium coummia, Spiniferella cornuta, Chichaouadinium vestitum, Dinopterygium alatum and Litosphaeridium arundum. The upper Albian (3406.5 - 3408 m) is characterized by the FOs of marker taxa: Cyclonephelium chabaca, Cribroperidinium auctificum and Chichaouadinium vestitum. Lastly, the upper Albian-lower Cenomanian transition is defined between 3404 m and 3406.50 m, as suggested by the FOs of Chichaouadinium boydii, Dinopterygium tuberculatum, Sepispinula ancorifera, Litosphaeridium conispinum, Prolixosphaeridium conulum and Xenascus ceratioides.

关键词： Morocco Tarfaya-Laayoune-Boujdour Basin Albian-Cenomanian Transition Dinoflagellate Cysts Palynostratigraphy

Optimized Energy Efficient Strategy for Data Reduction Between Edge Devices in Cloud-IoT

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Computers, Materials & Continua 2022年第7期72卷 125-140页

作者： Dibyendu Mukherjee Shivnath Ghosh Souvik Pal D.Akila N.z.Jhanjhi Mehedi Masud mohammed A.Alzain Department of Computer Science and Engineering Brainware UniversityBarasat700125India Department of Computer Science and Engineering Global Institute of Management and TechnologyKrishnanagar741102India Department of Information Technology School of Computing SciencesVels Institute of ScienceTechnology&Advanced StudiesChennai600117India School of Computer Science and Engineering SCE Taylor’s UniversitySubang Jaya47500SelangorMalaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Numerous Internet of Things(IoT)systems produce massive volumes of information that must be handled and answered in a quite short *** growing energy usage related to the migration of data into the cloud is one of the biggest *** computation helps users unload the workload again from cloud near the source of the information that must be handled to save time,increase security,and reduce the congestion of ***,in this paper,Optimized Energy Efficient Strategy(OEES)has been proposed for extracting,distributing,evaluating the data on the edge *** the initial stage of OEES,before the transmission state,the data gathered from edge devices are supported by a fast error like reduction that is regarded as the largest energy user of an IoT *** initial stage is followed by the reconstructing and the processing *** processed data is transmitted to the nodes through controlled deep learning *** entire stage of data collection,transmission and data reduction between edge devices uses less *** experimental results indicate that the volume of data transferred decreases and does not impact the professional data performance and predictive *** consumption of 7.38 KJ and energy conservation of 55.57 kJ was found in the proposed OEES *** accuracy is 97.5 percent,data performance rate was 97.65 percent,and execution time is 14.49 ms.

关键词： Energy efficient internet of things transmission performance cloud computing edge devices

Tracking Dengue on Twitter Using Hybrid Filtration-Polarity and Apache Flume

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Computer Systems Science & Engineering 2022年第3期40卷 913-926页

作者： Norjihan Binti Abdul Ghani Suraya Hamid Muneer Ahmad Younes Saadi N.z.Jhanjhi mohammed A.Alzain Mehedi Masud Department of Information Systems Faculty of Computer Science&Information TechnologyUniversiti Malaya50603Kuala LumpurMalaysia School of Computer Science and Engineering SCE Taylor’s UniversitySubang Jaya47500Malaysia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The world health organization(WHO)terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific *** and accurate detection of spread in affected regions can save precious *** the severity of the disease,a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text ***,the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data,as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights from the data are *** research study proposes a sentiment analysis polarity approach for collecting data and extracting relevant information about dengue via Apache *** method consists of two main parts:the first part collects data from social media using Apache Flume,while the second part focuses on querying and extracting relevant information via the hybrid filtration-polarity algorithm using Apache *** overcome the noisy and unstructured nature of the data,the process of extracting information is characterized by pre and post-filtration *** a result,only with the integration of Flume and Hive with filtration and polarity analysis,can a reliable sentiment analysis technique be offered to collect and process large-scale data from the social *** introduce how the Apache Hadoop ecosystem–Flume and Hive–can provide a sentiment analysis capability by storing and processing large amounts of *** important finding of this paper is that developing efficient sentiment analysis applications for detecting diseases can be more reliable through the use of the Hadoop ecosystem components than through the use of normal machines.

关键词： Big data analysis data filtration text analysis sentiment analysis social media event detection

Nd-doped NiFe_(2)O_(4) and its composite with CNTs to tune photocatalytic activity

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Journal of Rare Earths 2023年第12期41卷 1919-1928,I0004页

作者： Fatimah mohammed AAlzahrani Amna Irshad Sonia zulfiqar z.A.Alrowaili Noor ul Ain Asima Anwar Muhammad Farooq Warsi M.S.Al-Buriahi Department of Chemistry CollegeofSciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabi Institute of Chemistry Baghdad-ul-Jadeed CampusThe Islamia University of BahawalpurBahawalpur6310Pakistan Department of Chemistry Faculty of ScienceUniversity of Ostrava30.Dubna 22Ostrava70103Czech Republic Department of Chemicaland Biological Engineering Iowa State UniversitySweeney Hall618 Bissll RoadAmesIowa 50011United States Department of Physics College of ScienceJouf UniversityPo.Box 2014SakakaSaudi Arabia Institute of Physics Baghdad-ul-Jadeed CampusThe Islamia University of BahawalpurBahawalpur63100Pakistan Department of Physics Sakarya UniversitySakaryaTurkey

Rare earth-doped spinel nano ferrites are attaining importance as heterogeneous nanocatalysts for the degradation of organic *** earth metal doping increases the electrical and optical properties,as well as the surface-to-volume ratio of the bare *** this work,NiFe_(2)O_(4)(NF) and Nd-NiFe_(2)O_(4)(NF-1) were successfully synthesized via the co-precipitation *** nanotubes(CNT)-based nanocomposite(NF-2) was prepared using the ultra-sonication *** prepared materials were analyzed via various physiochemical *** degradation efficiency of these materials was analyzed for the degradation of Rhodamine B,methylene blue,and benzoic acid,NF-2 shows the highest efficiency among all the prepared ***-2 shows 83.87%,90.80%,and 66.96% degradation of Rhodamine B,methylene blue,and benzoic acid,*** reason for the superior activity of NF-2 is the existence of rare earth Nd ions and *** surface area of NF increases due to the presence of carbon nanotubes and enhanced surface area provides more active sites for the degradation reaction.

关键词： XRD Carbon nanotubes Benzoic acid Photo-degradation Visible light Rare earths

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