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Anomalous Situations Recognition in Surveillance Images Using Deep Learning

Computers, Materials & Continua 2023年第7期76卷 1103-1125页

作者： qurat-ul-ain arshad Mudassar Raza Wazir Zada Khan Ayesha Siddiqa Abdul Muiz Muhammad Attique Khan Usman Tariq Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah Campus47040Pakistan Deptartment of Computer Science University of WahWah Cantt47040Pakistan Deptartment of Computer Science HITEC UniversityTaxila47080Pakistan Management Information System Department College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj 16278Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Anomalous situations in surveillance videos or images that may result in security issues,such as disasters,accidents,crime,violence,or terrorism,can be identified through video anomaly ***,differentiat-ing anomalous situations from normal can be challenging due to variations in human activity in complex environments such as train stations,busy sporting fields,airports,shopping areas,military bases,care centers,*** learning models’learning capability is leveraged to identify abnormal situations with improved *** work proposes a deep learning architecture called Anomalous Situation Recognition Network(ASRNet)for deep feature extraction to improve the detection accuracy of various anomalous image *** proposed framework has five *** the first step,pretraining of the proposed architecture is performed on the CIFAR-100 *** the second step,the proposed pre-trained model and Inception V3 architecture are used for feature extraction by utilizing the suspicious activity recognition *** the third step,serial feature fusion is performed,and then the Dragonfly algorithm is utilized for feature optimization in the fourth ***,using optimized features,various Support Vector Machine(SVM)and K-Nearest Neighbor(KNN)based classification models are utilized to detect anomalous *** proposed framework is validated on the suspicious activity dataset by varying the number of optimized features from 100 to *** results show that the proposed method is effective in detecting anomalous situations and achieves the highest accuracy of 99.24%using cubic SVM.

关键词： Anomaly detection anomalous events anomalous behavior anomalous objects violence detection deep learning

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

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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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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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Ionic potency regulation of coagulation bath induced by saline solution to control over the pore structure of PBI membrane for highperformance lithium metal batteries

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Journal of Energy Chemistry 2024年第7期94卷 288-298页

作者： arshad Hussain Waseem Raza Andleeb Mehmood Sana Jalees Lihong Ao Yonggui Deng Aymeric Ramiere Xingke Cai Dongqing Liu College of Civil and Transportation Engineering Shenzhen UniversityShenzhen 518060GuangdongChina Institute for Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina Institute of Carbon Neutrality Zhejiang Wanli UniversityNingbo 315100ZhejiangChina College of Light Industry and Chemical Engineering Dalian Polytechnic UniversityDalian 116034LiaoningChina College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060GuangdongChina College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060GuangdongChina

In this study,we have explored the use of water as a non-solvent for tuning the microstructure of poly-benzimidazole(PBI)membranes,which are potential separators for lithium metal batteries(LMBs).The traditional method for membrane synthesis called nonsolvent-induced phase separation(NIPS),usually relies on hazardous and costly organic *** dissolving sodium chloride(Nacl)in water,we could adjust the water ionic potency and the exchange speed of the non-solvent with the DMAC solution to change the micropore structure of the PBI *** increasing Nacl concentration,the micro-pores in the PBI membrane transitioned from finger-like to sponge-like *** to com-mercial separators like the Celgard separator,the PBI membrane with sponge-like micropores exhibited better regulation of lithium deposition and improved Li^(+) transportation capability due to its good wetta-bility with the ***,the PBI membrane-based Li/Li symmetric cell and Li/LiFePO_(4) full cell demonstrated superior performance compared to the Celgard-based *** research proposes an eco-friendly and scalable synthetic approach for fabricating commercial separators for LMBs,addressing the issue of lithium dendrite growth and improving overall battery safety and performance.

关键词： Lithium metal-based battery Salt-induced Polybenzimidazole Tunablemorphology lonic potency

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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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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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