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Sedimentary facies analysis of a thin-bed-dominated turbidite succession in the Miocene Temburong Formation,Kampung Bebuloh,Labuan Island,Malaysia

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Journal of Palaeogeography 2024年第3期13卷 401-429页

作者： farah Syafira Burhanuddin Meor Hakif Amir Hassan Department of Geology Faculty of ScienceUniversiti Malaya50603 Kuala LumpurMalaysia

Thin-bedded turbidites are important hydrocarbon-bearing reservoirs in many mature fields throughout the *** type of turbidite depositional setting strongly influences vertical and horizontal continuity of the ***,distinguishing between lobe and levee associated thin-bedded turbidites remains challenging due to their generally similar facies *** study aims to contribute some insights to this problem by conducting a detailed bed-scale facies analysis on the Early Miocene Temburong Formation exposed at Kampung Bebuloh,Labuan Island,Malaysia,which may uncover features that can help in differentiating between both depositional *** facies are recognized in the Temburong Formation,which are interpreted as low density turbidites(F1-F4),hybrid event beds(F5),and sustained turbidites(F6).Detailed facies and ichnology analysis reveal features which are consistent with a lobe fringe deposit rather than leveeassociated environment interpretation,including tabular bed geometries,presence of hybrid event beds,and the absence of thick-bedded channel-fill *** facies associations are identified and interpreted as representing sub-environments within an overall lobe depositional setting.A diverse trace fossil assemblage,comprising the Nereites ichnofacies is consistent with a deep marine *** identification of the Paleodictyon and Nereites sub-ichnofacies indicates a distal turbidite system setting,most likely lobe *** on the thick accumulation of FA2 and FA3 and no distinct observable vertical trend,the Early Miocene Temburong Formation in Labuan is interpreted as turbidites deposited at the fringes of lobe complexes rather than a single lobe *** works into the Temburong Formation in SW Labuan proposed a middle slope to proximal basin floor setting where the thin-bedded intervals were interpreted as potentially representing either levee deposits or the fringes of confined lobe ***

关键词： Facies analysis Trace fossils Depositional lobes Hybrid event beds Lobe fringe Temburong formation Thin-bedded turbidite

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： farah Mohammad Saad Al-Ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Optimizing wind farm layout for enhanced electricity extraction using a new hybrid PSO-ANN method

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Global Energy Interconnection 2024年第3期7卷 254-269页

作者： Mariam El Jaadi Touria Haidi Abdelaziz Belfqih Mounia farah Atar Dialmy LAGES Laboratory Hassania School of Public Works(EHTP)Casablanca 20230Morocco LESE Laboratory National School of Electricity and Mechanics(ENSEM)Casablanca 20100Morocco LAGCET Laboratory Hassania School of Public Works(EHTP)Casablanca 20230Morocco

With the growing need for renewable energy,wind farms are playing an important role in generating clean power from wind *** best wind turbine architecture in a wind farm has a major influence on the energy extraction *** paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization(PSO)and artificial neural networks(ANNs).The PSO method was used to explore the solution space and develop preliminary turbine layouts,and the ANN model was used to fine-tune the placements based on the predicted energy *** proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical *** efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches,giving exciting prospects for developing more efficient and sustainable wind *** integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both ***,this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency.A notable increase in power generation is observed across various *** percentage increase in the power generation ranged from approximately 7.7%to 11.1%.Owing to its versatility and adaptability to site-specific conditions,the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.

关键词： Layout optimization Turbine placement Wind energy Hybrid optimization Particle swarm optimization Artificial neural networks Renewable energy Energy efficiency

Mapping lineaments using Landsat 8 OLI and SRTM data;a case study of the eastern part of the Ouarzazate Basin,Morocco

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Journal of Mountain Science 2024年第3期21卷 987-1003页

作者： MOUJANE Said ALGOUTI Ahmed ALGOUTI Abdellah farah Abdelouahed ABOULFARAJ Abdelfatah NAFOURI Imane Geoscience Geotourism Natural Hazards and Remote Sensing Laboratory(2GRNT) Department of GeologyFaculty of Sciences SemlaliaUniversity of Cadi AyyadBP 239040000MarrakechMorocco

The integration of remote sensing and geographic information system(GIS)was employed in this study to delineate the structural lineaments within the eastern section of the Ouarzazate Basin,situated between the southern front of the Central High Atlas and the northern slopes of the Eastern Anti-Atlas(also known as the Saghro Massif).To achieve this objective,Landsat 8 Operational Land Imager(OLI)and Shuttle Radar Topography Mission(SRTM)data were *** Component Analysis(PCA)was computed and a directional filter was applied to the first PCA and the panchromatic band(B8).Additionally,shading was applied to the SRTM data in four directions;N0°,N45°,N90°,N135°.After removing of the non-geological linear structures,the results obtained,using the automatic extraction method,allowed us to produce a synthetic map that included 1251 lineaments with an average length of 1331 m and was dominated by NE-SW,ENE-WSW and E-W directions,***,the high lineament density is clearly noted in the Anti-Atlas(Saghro Massif)and at the level of the northern part,extending from the Ait Ibrirne to Arg-Ali Oubourk *** lineament density can always be found around the major faults affecting this *** data collected during the field investigations and from geological maps show that the major direction of the faults and structural accidents range mostly between N45°,N70°and N75°.The correlation of remote sensing results with those collected in the field shows a similarity and coincidence with each *** these results,it is possible to consider the automatic extraction method as a supplementary kind that can serve classical geology by quickly enriching it with additional *** shown in this work,this method provides more information when applied in arid areas where the fields are well outcropped.

关键词： Remote sensing GIS Landsat 8 OLI SRTM Ouarzazate Basin Central High Atlas

Phishing Attacks Detection Using EnsembleMachine Learning Algorithms

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Computers, Materials & Continua 2024年第7期80卷 1325-1345页

作者： Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Marwan Abu-Zanona Bassam Mohammad Elzaghmouri farah H.Zawaideh Mouiad Fadeil Alawneh Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26110Jordan Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjloun26767Jordan

Phishing,an Internet fraudwhere individuals are deceived into revealing critical personal and account information,poses a significant risk to both consumers and web-based *** indicates a persistent rise in phishing ***,these fraudulent schemes are progressively becoming more intricate,thereby rendering them more challenging to ***,it is imperative to utilize sophisticated algorithms to address this *** learning is a highly effective approach for identifying and uncovering these harmful *** learning(ML)approaches can identify common characteristics in most phishing *** this paper,we propose an ensemble approach and compare it with six machine learning techniques to determine the type of website and whether it is normal or not based on two phishing *** that,we used the normalization technique on the dataset to transform the range of all the features into the same *** findings of this paper for all algorithms are as follows in the first dataset based on accuracy,precision,recall,and F1-score,respectively:Decision Tree(DT)(0.964,0.961,0.976,0.968),Random Forest(RF)(0.970,0.964,0.984,0.974),Gradient Boosting(GB)(0.960,0.959,0.971,0.965),XGBoost(XGB)(0.973,0.976,0.976,0.976),AdaBoost(0.934,0.934,0.950,0.942),Multi Layer Perceptron(MLP)(0.970,0.971,0.976,0.974)and Voting(0.978,0.975,0.987,0.981).So,the Voting classifier gave the best *** in the second dataset,all the algorithms gave the same results in four evaluation metrics,which indicates that each of them can effectively accomplish the prediction ***,this approach outperformed the previous work in detecting phishing websites with high accuracy,a lower false negative rate,a shorter prediction time,and a lower false positive rate.

关键词： Social engineering attacks phishing attacks machine learning security artificial intelligence

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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Computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

High-speed silicon photonic electro-optic Kerr modulation

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Photonics Research 2024年第1期12卷 51-60页

作者： JONATHAN PELTIER WEIWEI ZHANG LEOPOLD VIROT CHRISTIAN LAFFORGUE LUCAS DENIEL DELPHINE MARRIS-MORINI GUY AUBIN farah AMAR DENH TRAN XINGZHAO YAN CALLUM G.LITTLEJOHNS CARLOS ALONSO-RAMOS KE LI DAVID J.THOMSON GRAHAM REED LAURENT VIVIEN University Paris-Saclay CNRSCentre for Nanoscience and Nanotechnology(C2N)Palaiseau 91120France University Grenoble Alpes CEALETIGrenoble 38000France Optoelectronics Research Centre Zepler Institute for Photonics and NanoelectronicsFaculty of Engineering and Physical SciencesUniversity of SouthamptonSouthampton SO171BJUK

Silicon-based electro-optic modulators contribute to easing the integration of high-speed and low-power consumption circuits for classical optical communications and data *** the plasma dispersion modulation,an alternative solution in silicon is to exploit the DC Kerr effect,which generates an equivalent linear electro-optical effect enabled by applying a large DC electric *** some theoretical and experimental studies have shown its existence in silicon,limited contributions relative to plasma dispersion have been achieved in high-speed modulation so *** paper presents high-speed optical modulation based on the DC Kerr effect in silicon PIN *** contributions of both plasma dispersion and Kerr effects have been analyzed in different waveguide configurations,and we demonstrated that the Kerr induced modulation is dominant when a high external DC electric field is applied in PIN ***-speed optical modulation response is analyzed,and eye diagrams up to 80 Gbit/s in NRZ format are obtained under a *** of 30 *** work paves the way to exploit the Kerr effect to generate high-speed Pockels-like optical modulation.

关键词： waveguide dispersion effect

Left bundle branch pacing vs biventricular pacing in heart failure patients with left bundle branch block:A systematic review and meta-analysis

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World Journal of Cardiology 2024年第1期16卷 40-48页

作者： farah Yasmin Abdul Moeed Rohan Kumar Ochani Hamna Raheel Malik Ali Ehtsham Awan Ayesha Liaquat Arisha Saleem Muhammad Aamir Nael Hawwa Salim Surani Department of Internal Medicine Yale University School of MedicineNew HavenCT 06511United States Department of Medicine Dow University of Health ScienceKarachi 74200SindhPakistan Department of Medicine SUNNY Upstate Medical UniversitySyracuseNY 13210United States Department of Cardiovascular Medicine Lehigh Valley Heart and Vascular InstituteAllentownPA 18105United States Department of Medicine Cleveland ClinicClevelandOH 44195United States Department of Medicine&Pharmacology Texas A&M UniversityCollege StationTX 77843United States

BACKGROUND Left bundle branch pacing(LBBP)is a novel pacing modality of cardiac resynchronization therapy(CRT)that achieves more physiologic native ventricular activation than biventricular pacing(BiVP).AIM To explore the validity of electromechanical resynchronization,clinical and echocardiographic response of *** Systematic review and Meta-analysis were conducted in accordance with the standard guidelines as mentioned in detail in the methodology *** In our analysis,the success rate of LBBP-CRT was determined to be 91.1%.LBBP CRT significantly shortened QRS duration,with significant improvement in echocardiographic parameters,including left ventricular ejection fraction,left ventricular end-diastolic diameter and left ventricular end-systolic diameter in comparison with *** A significant reduction in New York Heart Association class and B-type natriuretic peptide levels was also observed in the LBBP-CRT group vs BiVP-CRT ***,the LBBP-CRT cohort had a reduced pacing threshold at follow-up as compared to BiVP-CRT.

关键词： Left bundle branch pacing Biventricular pacing QRS duration Left ventricular ejection fraction Heart failure

The Experience and Impact of a Fitbit-Based Physical Activity and Sleep Hygiene Intervention for Older Adults Experiencing Cognitive Decline

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Advances in Aging Research 2024年第3期13卷 41-59页

作者： Kate Walker Chris Griffiths Jen Yates Louise Birkett-Swan farah Hina Chee Siang Ang Research and Innovation Department Northamptonshire Healthcare NHS Foundation Trust Northampton UK Institute of Mental Health University of Nottingham Nottingham UK Dementia and Older People’ s Psychology Provision Northamptonshire Healthcare NHS Foundation Trust Northampton UK School of Computing University of Kent Canterbury UK

Objectives: This study aimed to understand the experience and impact of a physical activity and sleep wrist-worn tracker (Fitbit)-based healthy lifestyle intervention for older patients attending a memory assessment service, who are experiencing cognitive impairment but do not receive a dementia diagnosis. Methods: A qualitative design was employed. Semi-structured interviews were conducted with a purposeful sample of thirteen participants recruited from a memory assessment service. Thematic analysis, that was data driven and inductive, was undertaken to analyse the data. Results: Two global themes were developed. “Understanding exercise and sleep as part of my lifestyle” was made up of themes representing how participants viewed exercise and sleep as part of their lifestyles in terms of acknowledging the positive impacts and the barriers to exercise and sleep. The second global theme “Understanding my experience of the healthy lifestyle intervention” was made up of themes that identified the positive impact of the intervention regarding improving health and wellbeing, enabling validation of proactive behaviours and motivation to engage in healthy lifestyle behaviours, so promoting positive behaviour change. Conclusion: Patients experiencing age-related cognitive impairment, applied and benefited from a healthy lifestyle Fitbit-based intervention to facilitate and promote physical activity, better sleep hygiene and healthy lifestyles.

关键词： Cognitive Impairment Healthy Lifestyle Intervention Fitbit Health and Wellbeing Behaviour Change