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Green hydrogen production from photovoltaic power station as a road map to climate change mitigation

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CLEAN ENERGY 2024年第2期8卷 156-167页

作者： Kamil, Kehinde Ridwan Samuel, Bassey Okon Khan, umar Edge Hill Univ Dept Comp Sci & Engn Ormskirk England ENEL Green Power Rome Italy Steelagon Engn Ltd Mat Res Lab Sabon Gari Kaduna State Nigeria

The increasing recognition of hydrogen as a critical element in the global net-zero transition and its clear role in decarbonizing challenging sectors coincide with the growing urgency to address climate change. Africa's favourable renewable-energy capacity, ranging from 28% to 36% for solar, has been reported by the global solar irradiance index. However, the majority of hydrogen production today relies on fossil fuels (96%), with only a small fraction (4%) being produced through water electrolysis. Even though there have been many studies on climate change mitigation with a focus on Africa, a green hydrogen production from a photovoltaic power station approach has not been reported. Also, literature with a focus on Nigeria is lacking. This study focuses on the African green hydrogen production industry, utilizing Nigeria as a case study to explore the feasibility of generating clean hydrogen vectors from a percentage of photovoltaic power output in various regions of the country through stand-alone solar grid electrification projects. Analyses of the usage and effectiveness of the produced hydrogen fuel in each region are carried out, with the highest region having an annual output of 12 247 278 kg of green hydrogen and 8 573 094 kg of ammonia and the lowest region having an output of 511 245 kg of green hydrogen and 357 871 kg of ammonia, and the expected production from the proposed usage of 50% of the power generation output of the installed 1.6-MWp and 80-kWp solar power minigrids in the regions is calculated. The analyses were repeated for the other considered regions in the country. The results showcased the enormous advantages of the electrolytic production of hydrogen and how the greener economy project can play a major role in mitigating climate change effects and overreliance on fossil fuels as the driver of the economy in many African countries. Nigeria is used as a case study for the African green hydrogen production industry to explore the feasibility

关键词： renewable energy photovoltaic climate change green hydrogen vector fossil fossil fuels decarbonization electrolysis AMMONIA WATER CELL

Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： umar Rashid Arfan Jaffar Muhammad Rashid Mohammed S.Alshuhri Sheeraz Akram Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Department of Radiological Sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. Secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, Histogram Oriented Surface Normal Vector (HOSNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. Smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding

Enhancing ChatGPT’s Querying Capability with Voice-Based Interaction and CNN-Based Impair Vision Detection Model

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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

Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes Mohammed Zakariah Syed umar Amin Zafar Iqbal Khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 311-329页

作者： umar Shafique Mohamed Mahyoub Al-Shamiri Ali Raza Emad Fadhal Muhammad Rafiq Nauman Ahmed Department of Mathematics National College of Business Administration and EconomicsLahore54660Pakistan Department of Mathematics Applied CollegeMahayl AssirKing Khalid UniversityAbha62529Saudi Arabia Department of Physical Sciences The University of ChenabGujrat50700Pakistan Department of Mathematics&Statistics College of ScienceKing Faisal UniversityP.O.Box 400Al-Ahsa31982Saudi Arabia Department of Computer Science and Mathematics Lebanese American UniversityBeirut1102-2801Lebanon Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics and Statistics University of LahoreLahore54000Pakistan

Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal *** is a devastating disease and remains a significant public health *** study investigates a bacterial meningitis model through deterministic and stochastic ***-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and *** model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric ***,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known *** and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic ***,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step *** addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is *** simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results.

关键词： Bacterial Meningitis disease stochastic delayed model stability analysis extinction and persistence computational methods

Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.Khan Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

Structural Geology and Chronology of Shear Zones along the Shangdan Suture in Qinling Orogenic Belt,China:Implications for Late Mesozoic Intra-Continental Deformation of East Asia

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Journal of Earth Science 2024年第2期35卷 376-393页

作者： Falak Sheir Wei Li Le Zhang Basil Alabowsh Liuqing Jiang Li Liang Sainan Gao Shair Baz umar Ashraf State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’an710069China Institute of Geology University of PunjabLahore45590Pakistan

The Shangdan suture zone(SDZ)in the Qinling orogenic belt(QOB)is a key to understanding the East Asia tectonic *** SDZ gives information about convergent processes between the North China Block(NCB)and South China Block(SCB).In the Late Mesozoic,several shear zones evolved along the SDZ boundary that helps us comprehend the collisional deformation between the NCB and SCB,which was neglected in previous *** shear zones play an essential role in the tectonic evolution of the East Asia *** study focuses on the deformation and geochronology of two shear zones distributed along the SDZ,identified in the Shaliangzi and Maanqiao *** shear sense indicators and kinematic vorticity numbers(0.54–0.90)suggest these shear zones have sinistral shear and sub-simple shear deformation *** quartz’s dynamic recrystallization and c-axis fabric analysis in the Maanqiao shear zone(MSZ)revealed that the MSZ experienced deformation under green-schist facies conditions at∼400–500℃.The Shaliangzi shear zone deformed under amphibolite facies at∼500–700℃.The^(40)Ar/^(39)Ar(muscovite-biotite)dating of samples provided a plateau age of 121–123 *** with previously published data,our results concluded that QOB was dominated by compressional tectonics during the Late Early ***,we suggested that the Siberian Block moved back to the south and Lhasa-Qiantang-Indochina Block to the north,which promoted intra-continental compressional tectonics.

关键词： Qinling orogenic belt Shangdan suture zone shear zone Late Mesozoic intra-continental deformation East Asia tectonics

CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify *** NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDS examines both risky and typical behavior using a variety of *** the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security

Comparative Analysis for the Development of a Green Building Rating System for Nigeria

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Journal of Civil Engineering and Architecture 2024年第7期18卷 340-347页

作者： Usman Aminu umar Department of Civil Engineering Universiti Teknologi PetronasTronoh 31750PerakMalaysia

The functionality of buildings depends on the climate they are subjected to,this means buildings constructed these days need to be built to perform efficiently within the current and future climate and with the aim of reducing the greenhouse emission induced on the *** order to lower CO_(2) emissions and assist in reinforcing the capability of cities to adapt to climate change whilst enhancing the quality of the built environment,it is vital to improve the environmental performance and energy efficiency in *** study aims to identify and compare existing GBRS(green building rating system)with Nigerian climatic *** criteria weighting was developed from the questionnaire supplying expert *** began with a comparative analysis of *** analysis was conducted to find the similarities and differences between existing rating systems and come up with an appropriate rating system for *** approaches included a fieldwork approach(pilot study,survey);questionnaire;and interviews,both structured and ***,the information generated in this pre-test investigation formed the conversational guide and described the decision to determine the main factors that should be involved in the new assessment system for Nigeria.

关键词： Green building GBRS climate change Nigeria