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Clinical and Brain Computed Tomographic Profile of Stroke Patients in a Tertiary Hospital, North Central Nigeria

World Journal of Neuroscience 2022年第4期12卷 187-202页

作者： Isaac Terkimbi Annongu Emmanuel Uzodinma Iwuozo mohammed oloje hameed Daniel Msuega Chia Sesugh Samuel mohammed Ferdinand Aondohemba Mbahon Department of Radiology College of Health Sciences Benue State University Makurdi Makurdi Nigeria Department of Internal Medicine College of Health Sciences Benue State University Makurdi Makurdi Nigeria Department of Internal Medicine Benue State University Teaching Hospital Makurdi Makurdi Nigeria

Background: Stroke is a common neurological disorder associated with high morbidity and mortality worldwide. Aim: The study set out to characterize the clinico-radiologic pattern of stroke patients as well as to determine the correlation between the clinical and computed tomographic (CT) scan findings in a tertiary hospital in Makurdi, North central Nigeria. Method: This was a retrospective study of 145 patients with clinically suspected stroke, who underwent CT imaging at the Benue State University Teaching Hospital, Makurdi Nigeria between December 2020 and June 2022. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 26. Results: Of the 145 clinically diagnosed cases of stroke, 122 (84.1%) were confirmed on CT. 7 (4.8%) were stroke mimics and 16 (11.0%) were normal. There were 65 (53.3%) males and 57 (46.7%) females with a male: female ratio of 1.1:1. The mean age at presentation was 58.7 ± 12.87 years with age range of 69 - 78 years being affected most. Few cases of stroke were seen below the age of fifty years. Ischaemic stroke was the commonest 77 (63.1%) followed by primary intracerebral haemorrhage (ICH) 38 (31.4%) then sub arachnoid haemorrhage (SAH) 5 (4.1%). Most infarcts were below 10 cm2, while for ICH volume those below 10 cm3 and above 100 cm3 occurred in equal proportion. Hypertension was the main risk factor for stroke with respective frequency of 31 (21.4%) and 94 (64.8%) in isolation or associated with other risk factors like Diabetes mellitus (DM), hyperlipidemia, alcohol, and smoking among others. There was significant correlation between clinical and radiological diagnosis of stroke (p < 0.05). Conclusion: The result showed slight male preponderance with majority of suspected stroke confirmed by CT;these were mostly of ischaemic type. There was significant correlation between clinical and radiologic diagnosis of stroke while hypertension was the main risk factor identified.

关键词： Stroke Risk Factors Computed Tomography Neuroimaging Makurdi

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A deep learning fusion model for accurate classification of brain tumours in Magnetic Resonance images

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 790-804页

作者： Nechirvan Asaad Zebari Chira Nadheef mohammed Dilovan Asaad Zebari Mazin Abed mohammed Diyar Qader Zeebaree Haydar Abdulameer Marhoon Karrar hameed Abdulkareem Seifedine Kadry Wattana Viriyasitavat Jan Nedoma Radek Martinek Department of Information Technology Lebanese French UniversityErbilIraq Department of Computer Science University of ZakhoZakhoKurdistan RegionIraq Department of Computer Science College of ScienceNawroz UniversityDuhokKurdistan RegionIraq Department of Artificial Intelligence College of Computer Science and Information TechnologyUniversity of AnbarRamadiIraq Department of Telecommunications VSB‐Technical University of OstravaOstravaCzech Republic Department of Cybernetics and Biomedical Engineering VSB‐Technical University of OstravaOstravaCzech Republic Department of Computer Network and Information Security Technical College of Informatics-AkreDuhok Polytechnic UniversityDuhokIraq Information and Communication Technology Research Group Scientific Research CenterAl‐Ayen UniversityThi‐QarIraq College of Computer Sciences and Information Technology University of KerbalaKarbalaIraq College of Agriculture Al‐Muthanna UniversitySamawahIraq Department of Applied Data Science Noroff University CollegeKristiansandNorway Faculty of Commerce and Accountancy Chulalongkorn Business SchoolChulalongkorn UniversityBangkokThailand

Detecting brain tumours is complex due to the natural variation in their location, shape, and intensity in images. While having accurate detection and segmentation of brain tumours would be beneficial, current methods still need to solve this problem despite the numerous available approaches. Precise analysis of Magnetic Resonance Imaging (MRI) is crucial for detecting, segmenting, and classifying brain tumours in medical diagnostics. Magnetic Resonance Imaging is a vital component in medical diagnosis, and it requires precise, efficient, careful, efficient, and reliable image analysis techniques. The authors developed a Deep Learning (DL) fusion model to classify brain tumours reliably. Deep Learning models require large amounts of training data to achieve good results, so the researchers utilised data augmentation techniques to increase the dataset size for training models. VGG16, ResNet50, and convolutional deep belief networks networks extracted deep features from MRI images. Softmax was used as the classifier, and the training set was supplemented with intentionally created MRI images of brain tumours in addition to the genuine ones. The features of two DL models were combined in the proposed model to generate a fusion model, which significantly increased classification accuracy. An openly accessible dataset from the internet was used to test the model's performance, and the experimental results showed that the proposed fusion model achieved a classification accuracy of 98.98%. Finally, the results were compared with existing methods, and the proposed model outperformed them significantly.

关键词： brain tumour deep learning feature fusion model MRI images multi‐classification

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EECLP: AWireless Sensor Networks Energy Efficient Cross-Layer Protocol

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Computers, Materials & Continua 2024年第8期80卷 2611-2631页

作者： mohammed Kaddi mohammed Omari Moamen Alnatoor LDDI Laboratory University of AdrarAdrar01000Algeria Computer Science and Engineering Department School of EngineeringAmerican University of Ras Al KhaimahRas Al Khaimah72603United Arab Emirates

Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks(WSN).A sensor network comprises several micro-sensors deployed randomly in an area of interest.A micro-sensor is provided with an energy resource to supply electricity to all of its ***,the disposed energy resource is limited and battery replacement is generally *** this restriction,the sensors must conserve energy to prolong their *** energy conservation strategies for WSNs have been presented in the literature,from the application to the physical *** of these solutions focus only on optimizing a single layer in terms of energy *** this research,a novel cross-layer technique for WSNs’effective energy usage is *** most energy consumption factors exist in the Medium Access Control(MAC)layer and network layer,our EECLP protocol(Energy Efficient Cross-Layer Protocol for Wireless Sensor Networks)integrates these two layers to satisfy energy efficiency *** gain access to the transmission channel,we implement a communication regime at the MAC layer based on CSMA/CA(Carrier Sense Multiple Access/Collision Avoidance)***,depending on the activity and a standby period,we employ the RTS/CTS(Request to Send/Clear to Send)method to prevent collisions and resolve hidden node concerns by utilizing the network allocation vector(NAV)to calculate the transmission *** a greedy strategy,we establish chains amongst cluster members to mitigate the issue of high energy consumption in routing *** objective function was utilized to determine the optimal cross-chain path based on the distances to the base station(BS)and residual energy(RE).The simulation,testing,and comparison of the proposed protocol to peer protocols have shown superior outcomes and a prolonged network *** the suggested protocol,the network lifetime increases by 10%compared to FAMACO(Fuzzy and Ant Col

关键词： WSN energy consumption MAC layer network layer EECLP energy-efficient lifespan

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Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

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Computers, Materials & Continua 2024年第4期79卷 875-907页

作者： mohammed Alatiyyah Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

In the contemporary era of technological advancement,smartphones have become an indispensable part of individuals’daily lives,exerting a pervasive *** paper presents an innovative approach to passenger countingonbuses throughthe analysis ofWi-Fi signals emanating frompassengers’mobile *** study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels,thereby addressing a crucial aspect of public *** proposed system comprises three crucial elements:Signal capture,data filtration,and the calculation and estimation of passenger *** pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts undermoderate-crowding conditions,with an average deviation of 20%from the ground truth and an accuracy rate ranging from 90%to 100%.This underscores its efficacy in scenarios characterized by moderate levels of ***,in densely crowded conditions,the system exhibits a tendency to overestimate passenger numbers,occasionally doubling the actual *** acknowledging the need for further research to enhance accuracy in crowded conditions,this study presents a pioneering avenue to address a significant concern in public *** implications of the findings are poised to contribute substantially to the enhancement of bus operations and service quality.

关键词： Public transportation digital environment passenger estimation signal capturing Wi-Fi

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Integrated photonic fractional convolution accelerator

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Photonics Research 2024年第8期12卷 1828-1839页

作者： KEVIN ZELAYA mohammed-ALI MIRI Department of Physics Queens College of the City University of New YorkQueensNew York 11367USA Physics Program The Graduate Center of the City University of New YorkNew YorkNew York 10016USA

An integrated photonic circuit architecture to perform a modified-convolution operation based on the discrete fractional Fourier transform(DFrFT) is introduced. This is accomplished by utilizing two nonuniformly coupled waveguide lattices with equally spaced eigenmode spectra, the lengths of which are chosen so that the DFrFT and its inverse operations are achieved. A programmable modulator array is interlaced so that the required fractional convolution operation is performed. Numerical simulations demonstrate that the proposed architecture can effectively perform smoothing and edge detection tasks even for noisy input signals, which is further verified by electromagnetic wave simulations. Notably, mild lattice defects do not jeopardize the architecture performance, showing its resilience to manufacturing errors.

关键词： fractional convolution utilizing

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Numerical investigation of the effects of soil-structure and granular material-structure interaction on the seismic response of a flat-bottom reinforced concrete silo

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Earthquake Engineering and Engineering Vibration 2024年第3期23卷 609-623页

作者： Sonia Benkhellat mohammed Kadri Abdelghani Seghir Laboratory of Solid Mechanics and Systems University of M’Hamed BougaraBoumerdes 35000Algeria Laboratory of Geomaterials Environment and DevelopmentUniversity of M’Hamed BougaraBoumerdes 35000Algeria Research Laboratory of Applied Hydraulics and Environment Faculty of TechnologyUniversity of BejaiaBejaia 06000Algeria

In this work,a numerical study of the effects of soil-structure interaction(SSI)and granular material-structure interaction(GSI)on the nonlinear response and seismic capacity of flat-bottomed storage silos is conducted.A series of incremental dynamic analyses(IDA)are performed on a case of large reinforced concrete silo using 10 seismic *** IDA results are given by two average IDA capacity curves,which are represented,as well as the seismic capacity of the studied structure,with and without a consideration of the SSI while accounting for the effect of *** curves are used to quantify and evaluate the damage of the studied silo by utilizing two damage indices,one based on dissipated energy and the other on displacement and dissipated *** cumulative energy dissipation curves obtained by the average IDA capacity curves with and without SSI are presented as a function of the base shear,and these curves allow one to obtain the two critical points and the different limit states of the *** is observed that the SSI and GSI significantly influence the seismic response and capacity of the studied structure,particularly at higher levels of ***,the effect of the SSI reduces the damage index of the studied structure by 4%.

关键词： reinforced concrete silo perfectly matched layers soil-structure interaction granular material-structure interaction effective seismic input method damage index

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Improved Dwarf Mongoose Optimization Algorithm for Feature Selection:Application in Software Fault Prediction Datasets

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Journal of Bionic Engineering 2024年第4期21卷 2000-2033页

作者： Abdelaziz I.Hammouri mohammed A.Awadallah Malik Sh.Braik mohammed Azmi Al-Betar Majdi Beseiso Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Scientific Research and Graduate Studies University of Prince Mugrin42241MedinaSaudi Arabia Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityAl-HusonIrbid21110Jordan

Feature selection(FS)plays a crucial role in pre-processing machine learning datasets,as it eliminates redundant features to improve classification accuracy and reduce computational *** paper presents an enhanced approach to FS for software fault prediction,specifically by enhancing the binary dwarf mongoose optimization(BDMO)algorithm with a crossover mechanism and a modified positioning updating *** proposed approach,termed iBDMOcr,aims to fortify exploration capability,promote population diversity,and lastly improve the wrapper-based FS process for software fault prediction *** gained superb performance compared to other well-esteemed optimization methods across 17 benchmark *** ranked first in 11 out of 17 datasets in terms of average classification ***,iBDMOcr outperformed other methods in terms of average fitness values and number of selected features across all *** findings demonstrate the effectiveness of iBDMOcr in addressing FS problems in software fault prediction,leading to more accurate and efficient models.

关键词： Dwarf mongoose optimization algorithm Optimization Feature selection Classification

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Comparative analysis on the performance of different types of input-and command-shaping controllers in minimizing payload residual vibration of an overhead crane with an inclined supporting track

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International Journal of Mechanical System Dynamics 2024年第1期4卷 22-33页

作者： mohammed Alfares Khaled Alhazza Mechanical Engineering Department College of Engineering and PetroleumKuwait UniversityKuwait CityKuwait

Reducing the effects of external disturbance on overhead crane systems is crucial,as they can impair the controller performance and cause excessive vibrations or oscillations of the *** such external disturbance is the inclination of the supporting track of the crane trolley,which causes the system dynamics model to *** open-loop control strategy is widely utilized to control the payload sway motion and generally does not require any alterations in the physical structure of a system or the installation of sensors and/or *** and command shaping are two common open-loop control techniques applied to control overhead *** this paper,the effect of moving an overhead crane system along an inclined supporting track is *** addition,the ability of different types of input-and command-shaping control schemes to suppress the residual vibrations due to trolley track inclination is *** types of input-shaping controllers,which are double-step,zero vibration,and one command waveform(WF)shaper based on a trigonometric function,are used and tested.A linear equation of motion of the overhead crane resting on an inclined surface is developed to simulate the overhead crane and payload *** effectiveness of the different types of open-loop controllers to suppress residual vibrations is verified by both simulation and experimental *** addition,a new WF command shaper is proposed and designed to overcome track inclination while eliminating payload residual vibration.A comprehensive comparative analysis,both numerically and experimentally,is performed on the new proposed shaper to measure its effectiveness in handling inclination when compared to other types of open-loop *** new shaper outperforms other controllers in eliminating payload residual vibration for a wider range of inclination angles.

关键词： overhead cranes open-loop control input and command shaping payload residual vibrations

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Kaoline-based catalyst for a high stability desulfurization of sour heavy naphtha in a three-phase oscillatory baffled reactor

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Particuology 2024年第1期84卷 249-260页

作者： Hassan M.Hmood Saba A.Gheni Safaa M.R.Ahmed Mudheher M.Ali Hamid Yonis Saleh mohammed H.mohammed Awad E.mohammed Marwan A.Mahomood Hiba R.mohammed Ahmed A.Hassan Adam Harvey North Refineries Company Ministry of OilIraq Chemical Engineering Department Tikrit UniversityIraq Ministry of Oil Iraq AL-Hawija Technical Institute Northern Technical UniversityMoselIraq School of Engineering Newcastle UniversityUK

To meet the rapidly increasing demand for energy and the dramatic depletion of conventional crude oil,it is imperative to utilize sour *** no coke being produced,oxidative desulfurization(ODS)of naphtha lowers its sulfur content and average molecular *** this article,we outline a method for heavy naphtha non-extractive ODS using a very stable *** technique involves the use of a solid catalyst with oxygen gas as the *** necessitated relatively high mixing intensities;hence a three-phase Oscillatory Baffled Reactor(OBR)was *** catalyst was based on the zeolite ZSM-5,prepared from natural kaolin by a series of delamination and activation steps and impregnated with Fe.A TiO2 nanolayer was applied,using the sol-gel method,to prevent rapid *** reactor performance was evaluated to minimize the sulfur content in the naphtha *** to the protective coating,the sulfur conversion stabilized at 90%.The results of this work establish the use of natural clay-based catalysts in a continuous,three-phase ODS,particularly with regard to proving long-term *** also showed that modest ODS can be achieved using an environmentally friendly oxidant,at mild operating conditions,whilst maintaining stability.

关键词： Natural kaoline Desulfurization Three-phase Oscillatory baffled reactor

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MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed Seraj Ali Safaa Sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios mohammed Ali mohammed Abazeed Department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBShield has the potential to significantly enhance the security and trustworthiness of

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

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