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Journal of Mountain Science 2024年第2期21卷 690-717页

作者： Furquan ahmad Pijush SAMUI S.S.MISHrA Department of Civil Engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** SS approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO *** ANFIS-PSO model exhibits exceptional accuracy(training r2=0.9011,rMSE=0.0549;testing r2=0.8968,rMSE=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo Simulation Subset Simulation Machine Learning Seismic coefficient

Novel Framework for an Intrusion Detection System Using Multiple Feature Selection Methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.E.M.Eljialy Mohammed Yousuf Uddin Sultan ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDSs. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Effect of coenzyme Q10 supplementation on post-vitrification mouse embryo development

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Asian pacific Journal of reproduction 2024年第3期13卷 126-132页

作者： Anisa-Annur S Wan-Hafizah WJ Nor-Ashikin MNK muhammad-Zaki r Faculty of Pharmacy and Health Sciences Royal College of Medicine PerakUniversiti Kuala Lumpur30450 IpohPerakMalaysia Maternofetal and Embryo research Group Faculty of MedicineUniversiti Teknologi MARASelangor BranchSungai Buloh Campus47000 Sungai BulohSelangorMalaysia

Objective:To investigate the effects of coenzyme Q10(CoQ10)supplementation on post-vitrification embryo development and gross ***:Balb/c mouse embryos were cultured in potassium simplex optimised medium(KSOM)with varying CoQ10 concentrations[0(control),20,40,and 60μM].The most effective CoQ10 concentration(40μM)was selected for subsequent post-vitrification morphology *** were randomly divided into four groups:Group A(non-vitrified without CoQ10),Group B(non-vitrified with CoQ10),Group C(vitrified without CoQ10),and Group D(vitrified with CoQ10),followed by vitrification at the 8-cell *** rates and development until the blastocyst stage were evaluated through morphological examinations using ASEBIr's system,distinguishing normal and abnormal ***:Supplementation of 40μM CoQ10 significantly increased blastocyst formation(95%)compared to the control group(92%),20μM(62%),and 60μM(56%)(Prification,Group D exhibited a significant increase in blastocyst formation(92%)compared to Group C(82%)(Prphological assessments indicated superior embryo quality in Group B over Group D during the cleavage stage,morula,and blastocyst(Promising potential to enhance preimplantation embryo development,increase blastocyst formation rates,and improve embryo quality *** offers a promising approach to mitigate oxidative stress on embryos,potentially improving overall assisted reproductive technology outcomes.

关键词： Coenzyme Q10 Antioxidant Embryo development Vitrification Morphology Assisted reproductive technology

Assessing Multidimensional Vulnerability of rural Areas to Flooding:An Index‑Based Approach

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International Journal of Disaster risk Science 2024年第1期15卷 88-106页

作者： Samavia rasool Irfan ahmad rana Hassam Bin Waseem Department of Urban and regional Planning School of Civil and Environmental Engineering(SCEE)National University of Sciences and Technology(NUST)Islamabad 44000Pakistan

Vulnerability assessment is essential for understanding and launching effective flood risk reduction *** study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab,Pakistan to external *** concept of vulnerability encompasses a range of dimensions,including physical,social,institutional,environmental,economic,and *** a composite index method,indices were developed for each dimension and combined to create a multidimensional measure of vulnerability.A sample of 365 communities was selected using the Yamane sampling technique,and data were collected through a questionnaire containing 65 indicators across all *** statistics and ANOVA tests were used to analyze the *** results show that communities near the Chenab river had higher attitudinal and institutional vulnerability compared to other *** attitudinal vulnerabilities were as sociated with poorly perceived flood risks and low preparedness measures,whereas institutional vulnerabilities were driven by conventional flood protection strategies,lack of institutional trust,and lack of flood risk *** research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.

关键词： Chenab river Flood hazard Indus river Pakistan-rural areas:Vulnerability to flooding

SNr and rSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory round Building Scenario over Lora Network

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Computers, Materials & Continua 2024年第8期80卷 1927-1945页

作者： muhammad Ayoub Kamal muhammad Mansoor Alam Aznida Abu Bakar Sajak Mazliham Mohd Su’ud Malaysian Institute of Information Technology(MIIT) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Depertment of Computer Science DHA Suffa UniversityKarachiSindh75500Pakistan riphah Institute of System Engineering(rISE) Faculty of ComputingRiphah International UniversityIslamabad46000Pakistan Malaysian France Institute(MFI) Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneyUltimoNSW 2007Australia

In situations when the precise position of a machine is unknown,localization becomes *** research focuses on improving the position prediction accuracy over long-range(Lora)network using an optimized machine learning-based *** order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over Lora technology,this study proposed an optimized machine learning(ML)based *** signal strength indicator(rSSI)data from the sensors at different positions was first gathered via an experiment through the Lora network in a multistory round layout *** noise factor is also taken into account,and the signal-to-noise ratio(SNr)value is recorded for every rSSI *** study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference *** findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

关键词： Indoor localization MKNN Lora machine learning classification rSSI SNr localization

(Sm/Eu/Tm)^(3+) doped tantalum semiconductor system for photovoltaic and electrochemical functionality amplification

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Journal of rare Earths 2024年第8期42卷 1586-1594,I0007页

作者： Shaan Bibi Jaffri Khuram Shahzad ahmad Isaac Abrahams Ibrahim A.A Materials and Environmental Chemistry Lab Lab-E21Department of Environmental SciencesFatima Jinnah Women UniversityRawalpindiPakistan School of Physical and Chemical Sciences Queen Mary University of LondonLondonUnited Kingdom Department of Botany and Microbiology College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

This work reports the synthesis,characterization,and energy focused applications of the novel lanthanides co-doped tantalum pentoxide hetero-system(Sm^(3+)-Eu^(3+)-Tm^(3+):Ta_(2)O_(5)).Ln^(3+)-doped Ta_(2)O_(5) express excellent opto-electronic features reflected by the narrow band gap energy of 3.87 *** vibrations confirm the presence of Ta-O-Ta and Ta-O *** synthesized system possesses orthorhombic geometry with 59.46 nm particle *** the smoother and compact morphology,the synthesized material succeeds in augmenting the performance of different systems aimed at energy *** ambient perovskite solar cell device fabricated with the Ln^(3+)-doped Ta_(2)O_(5) as an electron transport layer excels in achieving an efficiency and fill factor of 14.17% and 76% under artificial *** device was marked by the negligible hysteresis behavior showing profound photovoltaic *** electrochemical activity of the Ln^(3+)-doped Ta_(2)O_(5) decorated electrode was evaluated for electrical charge storage potential with pseudocapacitive behavior,With the highest specific capacitance of 355.39 F/g and quicker ionic diffusion rate,the designed electrode excels conventionally used ***-catalysis of water with Ln^(3+)-doped Ta_(2)O_(5) material indicates its capacity for H_(2) production with the lowest overpotential and Tafel slope values of 148 and 121.2 mV/dec,while the O_(2) generation is comparatively *** the stable electrochemical output,this rare earth modified material has the potential to replace conventionally used environmentally perilous and costly materials.

关键词： Lanthanide doping rare earth materials Perovskite solar cells Supercapacitors Water splitting

An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1051-1075页

作者： Shazia Shamas Surya Narayan Panda Ishu Sharma Kalpna Guleria Aman Singh ahmad Ali AlZubi Mallak ahmad AlZubi Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpuraPunjab140401India Higher Polytechnic School Universidad Europea del AtlánticoC/Isabel Torres 21Santander39011Spain Department of Engineering Universidad Internacional IberoamericanaAreciboPR00613USA Uttaranchal Institute of Technology Uttaranchal UniversityDehradunUttarakhand248007India Computer Science Department King Saud UniversityRiyadhSaudi Arabia Faculty of Medicine Jordan University of Science and TechnologyIrbidJordan

The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis andplanning intervention. This research work addresses the major issues pertaining to the field of medical imageprocessing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposesan improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. Thebetter resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In thisprocess, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarmintelligent techniques. The techniques experimented in this paper are K-means with Artificial Bee Colony (ABC),K-means with Cuckoo Search Algorithm (CSA), K-means with Particle Swarm Optimization (PSO), and Kmeanswith Firefly Algorithm (FFA). The testing and evaluation are performed on Early Lung Cancer ActionProgram (ELCAP) database. The simulation analysis is performed using lung cancer images set against metrics:precision, sensitivity, specificity, f-measure, accuracy,Matthews Correlation Coefficient (MCC), Jaccard, and *** detailed evaluation shows that the K-means with Cuckoo Search Algorithm (CSA) significantly improved thequality of lung cancer segmentation in comparison to the other optimization approaches utilized for lung cancerimages. The results exhibit that the proposed approach (K-means with CSA) achieves precision, sensitivity, and Fmeasureof 0.942, 0.964, and 0.953, respectively, and an average accuracy of 93%. The experimental results prove thatK-meanswithABC,K-meanswith PSO,K-meanswith FFA, andK-meanswithCSAhave achieved an improvementof 10.8%, 13.38%, 13.93%, and 15.7%, respectively, for accuracy measure in comparison to K-means segmentationfor lung cancer images. Further, it is highlighted that the proposed K-means with CSA have achieved a significantimprovement in accuracy, hence can be utilized by resea

关键词： Lesion lung cancer segmentation medical imaging meta-heuristic Artificial Bee Colony(ABC) Cuckoo Search Algorithm(CSA) Particle Swarm Optimization(PSO) Firefly Algorithm(FFA) segmentation

Phonon Thermal Transport at Interfaces of a Graphene/Vertically Aligned Carbon Nanotubes/Hexagonal Boron Nitride Sandwiched Heterostructure

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Chinese Physics Letters 2024年第1期41卷 57-62页

作者：李檬璘 muhammad Asif Shakoori 王瑞鹏李海鹏 School of Materials Science and Physics China University of Mining and TechnologyXuzhou 221116China

Molecular dynamics simulation is used to calculate the interfacial thermal resistance of a graphene/carbon nanotubes/hexagonal boron nitride(Gr/CNTs/hBN)sandwiched heterostructure,in which vertically aligned carbon nanotube(VACNT)arrays are covalently bonded to graphene and hexagonal boron nitride *** find that the interfacial thermal resistance(ITr)of the Gr/VACNT/hBN sandwiched heterostructure is one to two orders of magnitude smaller than the ITr of a Gr/hBN van der Waals heterostructure with the same plane *** is observed that covalent bonding effectively enhances the phonon coupling between Gr and hBN layers,resulting in an increase in the overlap factor of phonon density of states between Gr and hBN,thus reducing the ITr of Gr and *** addition,the chirality,size(diameter and length),and packing density of sandwich-layer VACNTs have an important influence on the ITr of the *** the same CNT diameter and length,the ITr of the sandwiched heterostructure with armchair-shaped VACNTs is higher than that of the sandwiched heterostructure with zigzag-shaped VACNTs due to the different chemical bonding of chiral CNTs with Gr and *** the armchair-shaped CNT diameter increases or the length decreases,the ITr of the sandwiched heterostructure tends to ***,the increase in the VACNT packing density also leads to a continuous decrease in the ITr of the sandwiched heterostructure,attributed to the extremely high intrinsic thermal conductivity of CNTs and the increase of out-of-plane heat transfer *** work may be helpful for understanding the mechanism for ITr in multilayer vertical heterostructures,and provides theoretical guidance for a new strategy to regulate the interlayer thermal resistance of heterostructures by optimizing the design of sandwich layer thermal interface materials.

关键词： sandwich shaped packing

Vision based intelligent traffic light management system using Faster r‐CNN

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 932-947页

作者： Syed Konain Abbas muhammad Usman Ghani Khan Jia Zhu raheem Sarwar Naif rAljohani Ibrahim AHameed muhammad Umair Hassan Department of Computer Science and Engineering University of Engineering and TechnologyLahorePakistan Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of ICT and Natural Sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Transportation systems primarily depend on vehicular flow on roads. Developed coun-tries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real‐time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real‐time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster r‐CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state‐of‐the‐art methodologies.

关键词： access control artificial intelligence computer vision intelligent control

Evolution of light deflection and shadow from a gauge-potential-like AdS black hole under the influence of a non-magnetic plasma medium

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Communications in Theoretical Physics 2024年第9期76卷 85-96页

作者： riasat Ali Xia Tiecheng muhammad Awais rimsha Babar Department of Mathematics Shanghai University and Newtouch Center for Mathematics of Shanghai University Department of Mathematics University of Engineering and Technology Department of Mathematics GC University Faisalabad Layyah Campus

We investigate the light deflection in the weak field approximation from the accelerating charged AdS black hole. For this purpose, we apply the Gauss–Bonnet theorem to calculate the light deflection in the weak field area and use the Gibbons–Werner approach to analyze the optical geometry of the accelerating charged AdS black hole in the non-magnetic plasma absence/presence of a non-magnetic medium. We also represent the graphical behavior of the light deflection angle w.r.t. the impact parameter. We also compute the light deflection angle using Keeton and Petters approximations under the impact of accelerating charged AdS black hole geometry. Furthermore, by using the ray-tracing approach, we determine the shadow in the nonmagnetic plasma presence and also demonstrate that graphical shadow has an impact on the gauge potential, non-magnetic plasma frequencies and charge.

关键词： accelerating charged AdS black hole deflection angle Gibbons-Werner approach ray-tracing approach shadow