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Tuning structural,electrical,dielectric and magnetic properties of Mg-Cu-Co ferrites via dysprosium(Dy^(3+))doping

Journal of Rare Earths 2024年第1期42卷 137-146,I0005页

作者： Maria Akhtar M.S.Hasan Nasir Amin N.A.Morley muhammad imran.arshad Department of Physics Government College UniversityFaisalabad38000Pakistan Department of Physics The University of Lahore53700Pakistan Department of Materials Science and Engineering The University of SheffieldS13JDUK Department of Physics&Astronomy University College LondonUK

In current research work,Dy3+substituted Mg0.5Cu0.25Co0.25Fe2-xDyxO4(0.0≤x≤0.04 with the step interval of 0.01)soft ferrites were synthesized by the sol-gel auto combustion *** prepared samples were characterized by the techniques using X-ray diffraction(XRD),scanning electron microscopy(SEM),energy dispersive X-ray spectroscopy(EDS),Fourier transform infrared(FTIR)spectroscopy,curre nt-voltage(Ⅰ-Ⅴ)measurement,LCR meter,vibrating sample magnetometer(VSM)and *** data reveal that the average crystallite size is 49.71 nm and the lattice constant is 0.83703 nm for sample x=*** non-uniform grain growth was demonstrated by micrographs and impurity-free elemental composition was observed from EDX *** DC resistivity has an increasing and decreasing trend in ferromagnetic and paramagnetic regions with an increase in ***,the high resistivity is observed with the order of 1010Ω·cm,and the activation energy is 0.944 eV for samples x=*** dielectric parameters including dielectric constant,dielectric losses,and impedance gradually decrease with the increase in frequency from 8 Hz to 8 *** minimum dielectric loss at high frequency is found for sample x=*** coercivity(Hc)and saturation magnetization(Ms)are found in the ranges of 520.82-544.02 Oe and 20.5841-21.1473 emu/g,*** observations confirm that dysprosium(x=0.03)doped MCC-soft ferrites may be applicable in transformer cores,microwave absorbance,and telecommunication devices.

关键词： Soft ferrites DC resistivity Dielectric loss Impedance Coercivity Rare earths

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Evaluation of soil loss severity and ecological restoration approach for sustainable agriculture in the Hindu Kush, Karakoram and Himalaya region

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Journal of Mountain Science 2024年第5期21卷 1509-1521页

作者： arshad ASHRAF imran AHMAD Climate Energy and Water Research InstituteNational Agricultural Research Centre(NARC)Islamabad 44000Pakistan

Soil erosion has resulted in removal of the topsoils containing fine soil particles and plant nutrients, causing decrease in soil fertility in the Hindu Kush, Karakoram and Himalaya(HKH) region. The existing production of cereal crop grains has been reduced to one third of the potential crop grains production owing to land degradation and poor farming practices. It is necessary to assess risk of soil loss and identify appropriate controlling measures to address issues of low agriculture productivity and water insecurity in the region. In the present study, severity of soil loss was predicted using Revised Universal Loss Equation(RUSLE) and ecological measures were identified for sustainable mountain agriculture in the HKH region of Upper Indus Basin, Pakistan. Overall 62.6% area was found to have very low risk of soil loss, i.e., 100 t/(ha·yr) in about 6.8% and 7.4% areas respectively. The mean rate of soil loss was about 41.9 t/(ha·yr) in the Hindu Kush, 31.1 t/(ha·yr) in the Himalayas, 18.8 t/(ha·yr) in the Karakoram and overall 29.7 t/(ha·yr) in the three HKH ranges. As such no considerable measures have been adopted by the communities for restoration of the degraded areas except raising fruit/farm trees and supporting limited social forestry for their livelihoods. The slopes cleared for cultivation and susceptible to erosion may be stabilized through sowing/planting of multi-purpose plant species and formation of proper bench terraces. The conservation of forest ecosystem and pastures at higher elevations would help in reducing overland water flow, risk of flash flood hazard and minimizing sediment loads in the downstream. It is essential to adopt site-specific resource conservation techniques and restore possible ecosystem health for sustainable agriculture and economic developm

关键词： Climate change Erodibility Indus basin Land degradation Slope stabilization

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Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

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Computers, Materials & Continua 2024年第5期79卷 3333-3353页

作者： Aiman muhammad arshad Bilal Khan Sadique Ahmad muhammad Asim Department of Computer Science City University of Science and Information TechnologyPeshawar25000Pakistan EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,***, the research on RomanUrdu is not up to the ***, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

关键词： Digital forensics author profiling for security AdaBoostM1 random forest ensemble learning

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ROBO-SPOT:Detecting Robocalls by Understanding User Engagement and Connectivity Graph

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Big Data Mining and Analytics 2024年第2期7卷 340-356页

作者： muhammad Ajmal Azad Junaid arshad Farhan Riaz College of Comnputer Science Birmingham City UniversityBirminghamB55JUUK School of Computer Science University of LincolnLincolnLN67TSUK

Robo or unsolicited calls have become a persistent issue in telecommunication networks,posing significant challenges to individuals,businesses,and regulatory *** calls not only trick users into disclosing their private and financial information,but also affect their productivity through unwanted phone ringing.A proactive approach to identify and block such unsolicited calls is essential to protect users and service providers from potential ***,this paper proposes a solution to identify robo-callers in the telephony network utilising a set of novel features to evaluate the trustworthiness of callers in a *** trust score of the callers is then used along with machine learning models to classify them as legitimate or *** use a large anonymized dataset(call detailed records)from a large telecommunication provider containing more than 1 billion records collected over 10 *** have conducted extensive evaluation demonstrating that the proposed approach achieves high accuracy and detection rate whilst minimizing the error ***,the proposed features when used collectively achieve a true-positive rate of around 97%with a false-positive rate of less than 0.01%.

关键词： social network analysis reputation unwanted calls robo-callers telephone network Spam Over Internet Technology(SPIT)

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Aberrant adult neurogenesis in intractable epilepsy:can GABAergic progenitor transplantation normalize this process?

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Neural Regeneration Research 2024年第7期19卷 1419-1420页

作者： muhammad N.arshad Janice R.Naegele Department of Biology Wesleyan UniversityMiddletownCTUSA Department of Neuroscience Tufts University School of MedicineBostonMAUSA

Temporal lobe epilepsy(TLE) is a common type of focal epilepsy characterized by seizure foci within the temporal *** surgical resection of the foci is an established and effective approach for controlling seizures,both temporal lobes cannot be removed,due to their prominent roles in learning and ***,seizures induce changes to the temporal lobes that contribute to hyperexcitability,including mossy fiber sprouting,astrogliosis.

关键词： epilepsy progenitor seizures

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An Innovative Approach Using TKN-Cryptology for Identifying the Replay Assault

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Computers, Materials & Continua 2024年第1期78卷 589-616页

作者： Syeda Wajiha Zahra muhammad Nadeem Ali arshad Saman Riaz muhammad Abu Bakr Ashit Kumar Dutta Zaid Alzaid Badr Almutairi Sultan Almotairi Department of Computer Science Alhamd Islamic UniversityIslamabad44000Pakistan Department of Computer Science and Technology University of Science and Technology BeijingBeijing100083China Department of Computer Science National University of TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of TechnologyIslamabad44000Pakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic University of MadinahMedinah42351Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

Various organizations store data online rather than on physical *** the number of user’s data stored in cloud servers increases,the attack rate to access data from cloud servers also *** researchers worked on different algorithms to protect cloud data from replay *** of the papers used a technique that simultaneously detects a full-message and partial-message replay *** study presents the development of a TKN(Text,Key and Name)cryptographic algorithm aimed at protecting data from replay *** program employs distinct ways to encrypt plain text[P],a user-defined Key[K],and a Secret Code[N].The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm,and the length of the cipher text obtained is twice the length of the original *** the scenario that an attacker executes a replay attack on the cloud server,engages in cryptanalysis,or manipulates any data,it will result in automated modification of all associated values inside the *** mechanism has the benefit of enhancing the detectability of replay ***,the attacker cannot access data not included in any of the papers,regardless of how effective the attack strategy *** the end of paper,the proposed algorithm’s novelty will be compared with different algorithms,and it will be discussed how far the proposed algorithm is better than all other algorithms.

关键词： Replay attack malware message attack file encryption cryptology data security

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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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Review on current development of polybenzimidazole membrane for lithium battery

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Journal of Energy Chemistry 2024年第4期91卷 579-608页

作者： Yonggui Deng arshad Hussain Waseem Raza Xingke Cai Dongqing Liu Jun Shen College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060GuangdongChina Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management(IRC-HTCM) King Fahd University of Petroleum&MineralsKFUPM Box 504031261 DhahranSaudi Arabia Institute for Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina

With the rapid development of portable technology,lithium batteries have emerged as potential candidates for high-performance energy storage systems owing to their high energy density and cycling *** the key components of a lithium battery system,the separator plays a critical role as it directly influences the battery performance benchmark(cycling performance and safety).However,traditional polyolefin separators(polypropylene/polyethylene)are unable to meet the demands of highperformance and safer battery systems due to their poor electrolyte compatibility,thermal runaways,and ultimate growth of *** contrast,membranes fabricated using polybenzimidazole(PBI)exhibit excellent electrolyte wettability and outstanding thermal dimensional stability,thus holding great potential as separators for high-performance and high-safety *** this paper,we present a comprehensive review of the general requirements for separators,synthesis technology for separators,and research trends focusing PBI membranes in lithium batteries to alleviate the current commercial challenges faced by conventional polyolefin *** addition,we discuss the future development direction for PBI battery separators by considering various factors such as production cost,ecological footprint,preparation technology,and battery component *** exploring these perspectives,we aim to promote the continued application and exploration of PBI-based materials to advance lithium battery technology.

关键词： Lithium batteries Separators Porous separators Polybenzimidazole Membrane

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ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

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Intelligent Automation & Soft Computing 2024年第2期39卷 301-317页

作者： Aiman muhammad arshad Bilal Khan Khalil Khan Ali Mustafa Qamar Rehan Ullah Khan Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstanaKazakhstan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and *** improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and *** evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are *** findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,*** metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling *** study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and *** results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

关键词： Machine learning author profiling AdaBoostM1 random forest ensemble learning text classification

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Classification and Comprehension of Software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil Abbas arshad Ahmad Syed Muqsit Shaheed Rubia Fatima Sajid Shah Mohammad Elaffendi Gauhar Ali School of Computer Science and Technology Anhui UniversityHefei230039China School of Computing Sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer Science and IT University of LahoreLahore55150Pakistan Department of Computer Science Emerson UniversityPunjabMultan60000Pakistan EIAS(Emerging Intelligent Autonomous Systems)Data Science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

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