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Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble

Computers, Materials & Continua 2024年第2期78卷 2047-2066页

作者： muhammad Rizwan muhammad Faheem Mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran ashraf Department of Artificial Intelligence The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Information Technology Khwaja Fareed University of Engineering and ITRYKhan64200Pakistan Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Signal Theory and Communications and Telematic Engineering Unviersity of ValladolidPaseo de Belén 15Valladolid47011Spain Faculty of Social Science and Humanities Universidad Europea del Atlántico Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaCampeche24560México Fundación Universitaria Internacional de Colombia Bogotá111611Colombia Universidad Internacional Iberoamericana AreciboPuerto Rico00613USA Universidade Internacional do Cuanza Cuito46703Angola Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541South Korea

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media *** study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the ***,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic *** baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the *** FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to ***,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual *** proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText *** proposed model better captures the contextual features of the relatively small sample class and aids in the detection of

关键词： Depression classification deep learning FastText machine learning

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Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： Samar M.Alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed Ali muhammad irfan Abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various *** resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain *** plays a crucial role in the diagnosis of brain tumors and the examination of other brain ***,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely ***,early diagnosis of brain tumors is intricate,necessitating the use of computerized *** research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain *** proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third *** final step involves classification using the Support Vector Machine(SVM)*** classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)*** proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of ***,this method exhibits a shorter processing time of 0.44 s compared to existing *** performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and *** enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classi

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

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Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3513-3534页

作者： Nazik Alturki Abdulaziz Altamimi muhammad Umer Oumaima Saidani Amal Alshardan Shtwai Alsubai Marwan Omar Imran ashraf Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department College of Computer Science and Engineering University of Hafr Al-BatinHafarAl-Batin39524Saudi Arabia Department of Computer Science&Information Technology The Islamia University of BahawalpurP.O.Box 63100BahawalpurPakistan Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Information Technology and Management Illinois Institute of TechnologyChicagoIL 60616-3793USA Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate *** learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD *** study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning *** research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for ***,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(SMOTE)is used for class-imbalance *** ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning *** proposed TrioNet using KNN imputer and SMOTE outperformed other models with 98.97%accuracy for *** in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD.

关键词： Precisionmedicine chronic kidney disease detection SMOTE missing values healthcare KNNimputer ensemble learning

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Mechanical performance of cold mix asphalt containing cup lump rubber as a sustainable bio-modifier

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 424-440页

作者： Syed Abdul Ghafar muhammad Naqiuddin Mohd Warid Norhidayah Abdul Hassan Zulfiqar Ali Jattak ashraf Abdalla Mohammed Radwan Faculty of Civil Engineering Universiti Teknologi MalaysiaSkudai 81310Malaysia Department of Civil Engineering Balochistan University of Information TechnologyEngineering&Management SciencesQuettaPakistan Department of Civil Engineering Balochistan University of Engineering and TechnologyKhuzdarPakistan Department of Civil Engineering Faculty of EngineeringUniversity of TripoliTripoliLibya

The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional benefits,CMA has attracted little attention due to its inferior ***'s performance is enhanced using a sustainable binder bio-modifier,natural cup lump rubber(CLR)is one of *** study evaluated the tensile properties,rutting,moisture susceptibility,and adhesion properties of CLR-modified CMA(CMA-CR).The tensile property was enhanced by 26%due to CLR ***-CR had excellent rutting resistance of less than 2 mm rut depth at 10,000 load cycles,showing 70%improvement compared with conventional *** susceptibility evaluation indicated that CMA-CR had tensile strength ratio(TSR)value of 104%,satisfying the minimum 80%requirement of AASHTO *** also retained more than 96%bitumen *** moisture damage resistance was improved by 12%and 10%in terms of TSR and stripping,*** durability results revealed that the CMA-CR mixture prevented higher mass loss,representing 14%improvement compared with conventional CMA.

关键词： Cup lump rubber Cup lump modified cold mix asphalt Moisture damage Tensile property Rutting Digital imaging

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib Mushtaq muhammad irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1893-1932页

作者： Nadeem Salamat muhammad Kamran Shahzaib ashraf Manal Elzain Mohammed Abdulla Rashad Ismail Mohammed M.Al-Shamiri Institute of Mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of Mathematics Thal University BhakkarPunjab30000Pakistan Department of Mathematics Faculty of Science and ArtsKing Khalid UniversityMuhayl Assir61913Saudi Arabia

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and *** paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse *** it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,*** use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying *** present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these *** operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and *** highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making *** use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted ***,we developed a novel technique by combining the IFSs with quaternion *** establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making *** the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately wo

关键词： Intuitionistic fuzzy set quaternion numbers fuzzy logic decision-making rough set

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Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

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Computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq muhammad Asif Shehzad ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

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Juvenile hormone induces reproduction via miR-1175-3p in the red imported fire ant, Solenopsis invicta

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Insect Science 2024年第2期31卷 371-386页

作者： Jie Chen Ziying Guan Yunjie Ma Qingxing Shi Ting Chen muhammad irfan WarisLihua Lyu Lihua Lyu Yongyue Lu Guojun Qi Institute of Plant Protection Guangdong Academy of Agricultural SciencesKey Laboratory of Green Prevention and Control on Fruits and Vegetables in South China Ministry of Agriculture and Rural AffairsGuangdong Provincial Key Laboratory of High Technology for Plant ProtectionGuangzhouChina Department of Entomology College of Plant ProtectionSouth China Agricultural UniversityGuangzhouChina

Juvenile hormone(JH)acts in the regulation of caste differentiation between queens and workers(i.e.,with or without reproductive capacity)during vitellin synthesis and oogenesis in social ***,the regulatory mechanisms have not yet been ***,we identified a highly expressed microRNA(miRNA),miR-1175-3p,in the red imported fire ant,Solenopsis *** found that miR-1175-3p is prominently present in the fat bodies and ovaries of ***,miR-1175-3p interacts with its target gene,broad-complex core(Br-C),in the fat *** utilizing miR-1175-3p agomir,we successfully suppressed the expression of the Br-C protein in queens,resulting in reduced vitellogenin expression,fewer eggs,and poorly developed ***,decreasing miR-1175-3p levels led to the increased expression of Br-C and vitellogenin in workers,triggering the“re-development”of the ***,when queens were fed with JH,the expression of miR-1175-3p decreased,whereas the expression of vitellogenin-2 and vitellogenin-3 ***,the suppression of fertility in queens caused by treatment with agomir miR-1175-3p was completely rescued by the increased vitellogenin expression induced by being fed with *** results suggest the critical role of miR-1175-3p in JH-regulated reproduction,shedding light on the molecular mechanism underlying miRNA-mediated fecundity in social insects and providing a novel strategy for managing ***.

关键词： juvenile hormone miR-1175-3p red imported fire ant reproduction social insects vitellogenin

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Multi-site Passivation of ZnO Metal Oxides via Biomolecules for Efficient and Highly Stable Organic Solar Cells

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Chinese Journal of Chemistry 2024年第14期42卷 1582-1592页

作者： irfan Ismail Maria Khalil Xiaomei Gao Xingze Chen muhammad Jawad Rong Huang Zhiyun Li Emmanuel Acheampong Tsiwah Wei-shi Li Qun Luo Chang-Qi Ma i-Lab&Printable Electronics Research Center Suzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)SuzhouJiangsu215123 China University of Chinese Academy of Sciences(UCAS) Beijing100040 China School of Nano-Tech and Nano-Bionics University of Science and Technology of China(USTC)HefeiAnhui230027 China Shanghai Institute of Organic Chemistry(SIOC) Chinese Academy of Sciences(CAS)Shanghai200032 China Vacuum Interconnected Nanotech Workstation(Nano-X) SuzhouJiangsu215123 China

ZnO nanoparticles(nps)among metal oxide(MOs)are proven to be essential electron transporting layers(ETLs)applied in organic solar cells(OSCs).However,intrinsic defects,interfacial charge recombination,and catalytic behavior towards the active layer restrict the applications of ZnO nps for efficient and long-term stable *** commonly available biomolecule cytidine 5'-monophosphate(CMP-OH)with phosphonic acid,its salt cytidine 5'-monophosphate disodium salt(CMP-ONa)with a phosphate group as an anchoring group and conjugated terminal functional in both analogous molecules provide carrier transfer bridge at bottom interface of the active *** theoretical investigations and characterizations have discovered the multi-site coordination of CMP-OH towards acceptor molecules and ZnO *** dual-side alignment of CMP analogous molecules hinders interfacial charge recombination and enhances charge transfer potential at ***,PM6:L8-BO-based OSCs with modified ETL obtain 18.13%efficiency,12%higher than that of unmodified *** higher efficiency,CMP-OH-based OSC devices illustrate remarkably improved thermal stability for 500 h at 85℃with 72%of initial PCE and operation stability for 2000 h with 90.1%of initial *** work reveals the passivation mechanism of multi-anchoring groups towards MOs and single-functional groups towards the active layer to optimize the interface for efficient and highly stable OSCs.

关键词： Organic solar cells Nanoparticles Nucleotides Interfacial interactions Surface chemistry Multi-site passivation

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Design and Synthesis of NiO@Co_(3)O_(4)@ZSM-5 Heterogeneous Multitask Hollow Structures for Tandem Catalysis

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Chemical Research in Chinese Universities 2024年第3期40卷 529-535页

作者： muhammad Waqas Interdisciplinary Research Center for Refining and Advanced Chemicals King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia

Precipitation and impregnation procedures unevenly distribute metals on zeolite,limiting chemical transformation in Lewis-acid,Brönsted-acid and metal-catalyzed tandem ***,heterogeneous multitask transition metals oxides@zeolites are promising catalysts for sustainable processes;nevertheless,synthesis is fascinating and ***,the construction of purposely designed multitask materials segregated in selective shells reveals the remarkable spatial organization of metals-zeolite,resulting in them being suitable for a wide range of tandem *** synthesis of multi-site catalysts begins with a universal wet chemistry approach that yields nickel oxide(NiO)***,the NiO crystals are stabilized using cationic dodecyltrimethylammonium bromide,followed by achieving cross-linking carbon growth by emulsion polymerization of glucose in hydrothermal treatment to yield uniformed NiO@carbon spheres(NiO@CSs).Next,sequential adsorption of cobalt cations and colloidal ZSM-5(1%in H_(2)O,mass fraction),followed by calcination in air,yielded NiO@cobalt oxide@zeolite denoted as NiO@Co_(3)O_(4)@ZEO hollow *** hollowing mechanism and materials segregation within shells are revealed by scanning and transmission electron microscopy,thermogravimetric analysis,and X-ray *** finding advances the rational synthesis of heterogenous core-shell hollow structures for various gas phase catalytic tandem reactions to yield valuable chemicals.

关键词： Multifunctional Core-shell hollow spheres Gas-phase reaction Valuable chemical

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