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天地万物守护海洋中与陆地上的动物

空中英语教室（高级版．彭蒙惠英语） 2024年第3期 28-30,46,47页

作者： sarah-mae McCullough 不详

如何在普吉特海湾友善地赏鲸,要去哪里赏鲸是游客询问有关西雅图的热门问题之一。一年内,虎鲸、座头鲸、小须鲸、灰鲸纷纷通过普吉特海湾,西雅图人不用走远就能看到。

关键词：灰鲸小须鲸天地万物西雅图普吉动物海湾

Predicting energy Consumption Using stacked LsTM snapshot ensemble

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Big Data Mining and Analytics 2024年第2期7卷 247-270页

作者： Mona Ahamd Alghamdi Abdullah s.A.L-Malaise AL-Ghamdi Mahmoud Ragab information systems Department Faculty of Computing and Information Technology(FCIT)King Abdulaziz University(KAU)Jeddah 21589Kingdom of Saudi Arabia information systems Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah 22246Kingdom of Saudi Arabia information Technology Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with Mathematics DepartmentFaculty of ScienceAl-Azhar UniversityNaser City 11884Egypt

The ability to make accurate energy predictions while considering all related energy factors allows production plants,regulatory bodies,and governments to meet energy demand and assess the effects of energy-saving *** energy consumption falls within normal parameters,it will be possible to use the developed model to predict energy consumption and develop improvements and mitigating measures for energy *** objective of this model is to accurately predict energy consumption without data limitations and provide results that are easily *** proposed model is an implementation of the stacked Long short-Term Memory(LsTM)snapshot ensemble combined with the Fast Fourier Transform(FFT)and *** and Berard’s individual Household electric-Power Consumption(iHePC)dataset incorporated with weather data are used to analyse the model’s accuracy with predicting energy *** model is trained,and the results measured using Root Mean square error(RMse),Mean Absolute error(mae),Mean Absolute Percentage error(MAPe),and coefficient of determination(R^(2))metrics are 0.020,0.013,0.017,and 0.999,*** stacked LsTM snapshot ensemble performs better than the compared models based on prediction accuracy and minimized *** results of this study show that prediction accuracy is high,and the model’s stability is high as *** model shows that high levels of accuracy prove accurate predictive ability,and together with high levels of stability,the model has good interpretability,which is not typically accounted for in ***,this study shows that it can be inferred.

关键词： energy consumption prediction Artificial intelligence(Ai) Deep Learning(DL) snapshot ensemble

Outsmarting Android Malware with Cutting-edge Feature engineering and Machine Learning Techniques

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Computers, Materials & Continua 2024年第4期79卷 651-673页

作者： Ahsan Wajahat Jingsha He Nafei Zhu Tariq Mahmood Tanzila saba Amjad Rehman Khan Faten s.A.lamri Faculty of information Technology Beijing University of TechnologyBeijing100124China Artificial intelligence and Data Analytics(AiDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of information sciences University of EducationVehari CampusVehari61100Pakistan Department of Mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy *** escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital *** methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false *** meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in *** proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data *** Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction *** study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert *** proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,*** empirical result shows thatthe RandomForest(RF)and support VectorMachine(sVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on mae,Mse,R2,and sensitivity parameters,resulting in a flawlessperformance for both *** app

关键词： Android malware detection machine learning sVC K-Nearest Neighbors(KNN) RF

Modeling of Total Dissolved solids (TDs) and sodium Absorption Ratio (sAR) in the edwards-Trinity Plateau and Ogallala Aquifers in the Midland-Odessa Region Using Random Forest Regression and eXtreme Gradient Boosting

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Journal of Geoscience and environment Protection 2024年第5期12卷 218-241页

作者： Azuka i. Udeh Osayamen J. imarhiagbe erepamo J. Omietimi Department of Geoscience University of Texas Permian Basin Odessa Texas USA Department of Geology University of Pretoria Pretoria South Africa

efficient water quality monitoring and ensuring the safety of drinking water by government agencies in areas where the resource is constantly depleted due to anthropogenic or natural factors cannot be overemphasized. The above statement holds for West Texas, Midland, and Odessa Precisely. Two machine learning regression algorithms (Random Forest and XGBoost) were employed to develop models for the prediction of total dissolved solids (TDs) and sodium absorption ratio (sAR) for efficient water quality monitoring of two vital aquifers: edward-Trinity (plateau), and Ogallala aquifers. These two aquifers have contributed immensely to providing water for different uses ranging from domestic, agricultural, industrial, etc. The data was obtained from the Texas Water Development Board (TWDB). The XGBoost and Random Forest models used in this study gave an accurate prediction of observed data (TDs and sAR) for both the edward-Trinity (plateau) and Ogallala aquifers with the Rsup>2sup> values consistently greater than 0.83. The Random Forest model gave a better prediction of TDs and sAR concentration with an average R, mae, RMse and Mse of 0.977, 0.015, 0.029 and 0.00, respectively. For the XGBoost, an average R, mae, RMse, and Mse of 0.953, 0.016, 0.037 and 0.00, respectively, were achieved. The overall performance of the models produced was impressive. From this study, we can clearly understand that Random Forest and XGBoost are appropriate for water quality prediction and monitoring in an area of high hydrocarbon activities like Midland and Odessa and West Texas at large.

关键词： Water Quality Prediction Predictive Modeling Aquifers Machine Learning Regression eXtreme Gradient Boosting

Artificial intelligence Prediction of One-Part Geopolymer Compressive strength for sustainable Concrete

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Computer Modeling in engineering & sciences 2024年第10期141卷 525-543页

作者： Mohamed Abdel-Mongy Mudassir iqbal M.Farag Ahmed.M.Yosri Fahad Alsharari saif eldeen A.s.Yousef Department of Civil engineering College of EngineeringJouf UniversitySakaka72388Saudi Arabia Department of Civil engineering University of Engineering and TechnologyPeshawar54890Pakistan Civil engineering Department Faculty of EngineeringAl-Azhar UniversityCairo11884Egypt Civil engineering Department Faculty of EngineeringAswan UniversityAswan81528Egypt

Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological *** terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part ***,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely ***,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GeP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part *** database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing *** performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(mae),and rootmean square error(RMse).in terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed *** and parametric analysis were also performed to identify the significant contributor to *** to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 *** water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.

关键词： Artificial intelligence techniques one-part geopolymer artificial neural network gene expression modelling sustainable construction polymers

Multifunctional, sustainable, and Biological Non-Ureolytic self-Healing systems for Cement-Based Materials

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engineering 2022年第6期8卷 217-237页

作者： Mohammad Fahimizadeh Pooria Pasbakhsh Lee sui mae Joash Ban Lee Tan R.K.singh Raman school of engineering Monash University MalaysiaBandar Sunway 47500Malaysia school of science Monash University MalaysiaBandar Sunway 47500Malaysia Tropical Medicine and Biology Multidisciplinary Platform Monash University MalaysiaBandar Sunway 47500Malaysia Department of Chemical engineering&Department of Mechanical and Aerospace engineering Monash UniversityClaytonVIC 3168Australia

Microbially induced calcium carbonate(CaCO_(3))precipitation(MiCP)has been investigated as a sustain-able alternative to conventional concrete remediation methods for improving the mechanical properties and durability of concrete *** date,urea-dependent MiCP is the most widely employed MiCP pathway in biological self-healing concrete research as its use has resulted in efficient CaCO_(3) precipita-tion ***_(3) is a byproduct of ureolysis,and can be hazardous to cementitious structures and the health of various ***,non-ureolytic bacterial concrete self-healing systems have been developed as eco-friendly alternatives to urea-dependent self-healing ***-ureolytic pathways can improve the physical properties of concrete samples and incorporate the use of waste materials;they have the potential to be cost-effective and ***,they can be applied in terrestrial and marine *** date,research on non-ureolytic concrete self-healing systems has been scarce compared to that on ureolytic *** article discusses the advances and challenges in non-ureolytic bacterial concrete self-healing studies and highlights the directions for future research.

关键词： self-healing concrete Mechanical properties Durability Non-ureolytic pathways Cement composite sustainability

Otologic and vestibular symptoms in COViD-19:A scoping review

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World Journal of Otorhinolaryngology-Head and Neck surgery 2022年第4期8卷 287-296页

作者： Kimberly mae C.Ong Teresa Luisa G.Cruz Philippine National ear institute National Institutes of HealthUniversity of the Philippines ManilaManilaPhilippines College of Medicine University of the Philippines ManilaManilaPhilippines Department of Otorhinolaryngology University of the Philippines-Philippine General HospitalManilaPhilippines

Background:Otologic and vestibular symptoms have been seen in patients confirmed to have COViD-19 *** discussion of these symptoms may provide insight into short-and long-term management for these ***:The aim of this review was to describe the otologic and vestibular symptoms that present in patients with *** primary outcomes of this review were onset,duration and clinical outcomes of these *** of evidence:Pub Med,APAMed Central,Herdin,CiNAHL,scopus,springer Link,ProQuest Coronavirus Research Database,and Google scholar were searched for the articles to be *** Criteria:studies included were those involving adult patients diagnosed with COViD-19 who experienced hearing loss,ear pain,ear discharge,otitis media,vertigo,or *** were eligible for inclusion if there was a description of the otologic dysfunction,specifically onset,duration,or clinical ***:The majority of patients who experienced hearing loss(68%),tinnitus(88%),vertigo/dizziness(30%),ear pain(8%),and discharge(100%)did so within a month of experiencing the typical symptoms of COViD-19.A majority also experienced complete resolution of their symptoms within 2 *** treatment for COViD-19 was usually provided but when specific diagnoses are made for these symptoms(e.g.,sudden sensorineural hearing loss,otitis media,vestibular neuritis),they are treated in the same manner as one would for non-COViD-19 cases,in addition to the management for *** certain cases,there may be a need for additional work-up to rule out other ***:Otologic and vestibular symptoms were present in COViD-19 patients,majority as part of the systemic nature of the *** onset,duration,and course were consistent with the natural history of a systemic viral ***-19 should be considered in any patient with a new-onset hearing loss,tinnitus,or vertigo/dizziness,even in the absence of infectious or respirato

关键词： COViD-19 dizziness hearing loss tinnitus vertigo

Usage of topical insulin for the treatment of diabetic keratopathy,including corneal epithelial defects

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World Journal of Diabetes 2023年第6期14卷 930-938页

作者： Ching Yee Leong Ainal Adlin Naffi Wan Haslina Wan Abdul Halim mae-Lynn Catherine Bastion Department of Ophthalmology Universiti Kebangsaan Malaysia Medical CentreKuala Lumpur 56000Wilayah PersekutuanMalaysia

BACKGROUND Diabetic keratopathy(DK)occurs in 46%-64%of patients with diabetes and requires serious *** patients with diabetes,the healing of corneal epithelial defects or ulcers takes longer than in patients without *** is an effective factor in wound *** ability of systemic insulin to rapidly heal burn wounds has been reported for nearly a century,but only a few studies have been performed on the effects of topical insulin(Ti)on the *** with Ti is effective in treating *** To review clinical and experimental animal studies providing evidence for the efficacy of Ti to heal corneal *** National and international databases,including PubMed and scopus,were searched using relevant keywords,and additional manual searches were conducted to assess the effectiveness of Ti application on corneal wound *** articles published from January 1,2000 to December 1,2022 were *** relevancy of the identified citations was checked against predetermined eligibility standards,and relevant articles were extracted and *** A total of eight articles were found relevant to be discussed in this review,including four animal studies and four clinical *** to the studies conducted,Ti is effective for corneal re-epithelialization in patients with diabetes based on corneal wound size and healing *** Available animal and clinical studies have shown that Ti promotes corneal wound healing by several *** use of Ti was not associated with adverse effects in any of the published *** studies are needed to enhance our knowledge and understanding of Ti in the healing of DK.

关键词： Diabetes mellitus Diabetic keratopathy Topical insulin Healing

Machine Learning and statistical Analysis in Groundwater Monitoring for Total Dissolved solids Assessment in Winkler County, Texas

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Journal of Geoscience and environment Protection 2024年第6期12卷 1-29页

作者： Azuka i. Udeh Osayamen J. imarhiagbe erepamo J. Omietimi Abdulqudus O. Mohammed Oluwatomilola Andre-Obayanju Department of Geoscience University of Texas Permian Basin Odessa USA Department of Geology University of Pretoria Pretoria South Africa Department of Geology University of Benin Benin Nigeria

This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved solids (TDs) in wells of the Permian basin, Winkler County, Texas. The data for this contribution was obtained from the Texas Water Development Board website (TWDB). Five hundred and ninety-three samples were obtained from two hundred and ninety-eight wells in the study area. The wells were drilled at different county locations into five aquifers, including Pecos Valley, Dockum, Capitan Reef, edward Trinity, and Rustler aquifers. A total of fourteen different water quality parameters were used, and they include Potential hydrogen (pH), sodium, Chloride, Magnesium, Fluoride, TDs, specific Conductance, Nitrate, Total Hardness, Calcium, Temperature, Well Depth, sulphate, and Bicarbonates. Four machine learning regression algorithms were developed to get a good model to help predict TDs in this area: Decision Tree regression, Linear regression, support Vector Regression, and K-nearest neighbor. The study showed that the Decision Tree produced the best model with attributes like the coefficient of determination R2 = 1.00 and 0.96 for the training and testing, respectively. it also produced the lowest score of mean absolute error mae = 0.00 and 0.04 for training and testing, respectively. This study will reduce the cost of obtaining different water quality parameters in TDs determination by leveraging machine learning to use only the parameters contributing to TDs, thereby helping researchers obtain only the parameters necessary for TDs prediction. it will also help the authorities enact policies that will improve the water quality in areas where drinking water availability is a challenge by providing important information for monitoring and assessing groundwater quality.

关键词： Machine Learning Regression Aquifers Winkler County sinkholes