检索结果-南通市图书馆

Sharp Bounds for Upper and Bottom Spectrum of Hermitizable Tridiagonal Matrices

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Mathematical Research with Applications 2025年第1期 125-132页

作者： Yueshuang LI Lingdi WANG school of Statistics Capital University of Economics and Business school of Mathematics and Statistics Henan University

We display sharp bounds for upper and lower spectrum of a Hermitizable tridiagonal matrix. The representations are brought to light by exploiting the characteristic for eigenpairs(eigenvalue and its corresponding eigenvector) of tridiagonal matrices, isospectral transforms and sharp bounds for speed stability of birth-death processes.

关键词：

Understanding the Language of ISIS:An Empirical Approach to Detect Radical Content on Twitter Using Machine Learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第2期66卷 1075-1090页

作者： Zia Ul Rehman Sagheer Abbas Muhammad Adnan Khan Ghulam Mustafa Hira Fayyaz Muhammad Hanif Muhammad Anwar Saeed school of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Sciences Bahria UniversityLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan school of Systems and Technology University of Management and TechnologyLahore54000Pakistan Department of CS&IT Virtual University of PakistanLahore54000Pakistan

The internet,particularly online social networking platforms have revolutionized the way extremist groups are influencing and radicalizing *** research reveals that the process initiates by exposing vast audiences to extremist content and then migrating potential victims to confined platforms for intensive ***,social networks have evolved as a persuasive tool for extremism aiding as recruitment platform and psychological ***,recognizing potential radical text or material is vital to restrict the circulation of the extremist *** aim of this research work is to identify radical text in social *** contributions are as follows:(i)A new dataset to be employed in radicalization detection;(ii)In depth analysis of new and previous datasets so that the variation in extremist group narrative could be identified;(iii)An approach to train classifier employing religious features along with radical features to detect radicalization;(iv)Observing the use of violent and bad words in radical,neutral and random groups by employing violent,terrorism and bad words *** research results clearly indicate that incorporating religious text in model training improves the accuracy,precision,recall,and F1-score of the *** a variation in extremist narrative has been observed implying that usage of new dataset can have substantial effect on classifier *** addition to this,violence and bad words are creating a differentiating factor between radical and random users but for neutral(anti-ISIS)group it needs further investigation.

关键词： Radicalization extremism machine learning natural language processing twitter text mining

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第2期66卷 1595-1612页

作者： Kashif Iqbal Sagheer Abbas Muhammad Adnan Khan Atifa Ather Muhammad Saleem Khan Areej Fatima Gulzar Ahmad school of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Sciences GC UniversityLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Comsats University IslamabadLahore CampusLahore54000Pakistan

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of ***-based target detection and object classification have been improved due to the development of deep learning *** fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise,well-engineered,and complete detection of objects,scene or *** target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion *** this study we examined to solve these problems described by(1)extracting region-of-interest in the images(2)vehicle detection based on instance segmentation,and(3)building deep learning model based on the key features obtained from input parking *** build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking *** augmentation techniques were performed using edge detection,cropping,refined by rotating,thresholding,resizing,or color augment to predict the region of bounding boxes.A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling,training,validating and testing on parking video frames through *** results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6%than previous reported ***,this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space *** results are verified using Python,TensorFlow,OpenCV computer simulation frameworks.

关键词： Smart parking-lot detection deep convolutional neural network data augmentation region-of-interest object detection

Error Detection and Pattern Prediction Through Phase II Process Monitoring

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第3期70卷 4781-4802页

作者： Azam Zaka Riffat Jabeen Kanwal Iqbal Khan Government Graduate College of Science Wahdat RoadLahorePakistan COMSATS University Islamabad Lahore CampusLahorePakistan Institute of business&Management University of Engineering and TechnologyLahorePakistan

The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function *** is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality *** current study introduces control charts that help the manufacturing concerns to keep the production process in *** presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their *** percentiles estimator and the modified maximum likelihood estimator are used to constructing the control *** findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weightedmoving average control charts based on the percentiles estimator and modified maximum likelihood ***,these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry.

关键词： Reflected power function distribution exponentially weighted moving average extended exponentially weighted moving averages modified maximum likelihood estimator percentile estimator

Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第2期66卷 1269-1282页

作者： Syeda Binish Zahra Muhammad Adnan Khan Sagheer Abbas Khalid Masood Khan Mohammed A.Al-Ghamdi Sultan H.Almotiri school of Computer Science National College for Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia

Biomechanics is the study of physiological properties of data and the measurement of human *** normal conditions,behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style,body movements in walking patterns,writing style and voice *** cannot perform any change in these inputs that make results reliable and increase the *** aim of our study is to perform a comparative analysis between the marker-based motion capturing system(MBMCS)and the marker-less motion capturing system(MLMCS)using the lower body joint angles of human gait *** both the MLMCS and MBMCS,we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity(walk and running).Using five state of the art machine learning algorithms,we obtained 44.6%and 64.3%accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm(two angles as features).In the second set of experiments,we used six machine learning algorithms to obtain 65.9%accuracy with the k-nearest neighbor(KNN)algorithm(two angles as features)and 74.6%accuracy with an ensemble ***,by increasing features(6 angles),we obtained higher accuracy of 99.3%in MBMCS for person recognition and 98.1%accuracy in MBMCS for activity recognition using the KNN *** is computationally expensive and if we redesign the model of OpenPose with more body joint points and employ more features,MLMCS(low-cost system)can be an effective approach for video data analysis in a person identification and activity recognition process.

关键词： Marker-based motion capturing system marker-less motion capturing system support vector machine K-nearest neighbor

Optimization of gob ventilation boreholes design in longwall mining

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Mining Science and Technology 2020年第6期30卷 811-817页

作者： Saqib Ahmad Saki Jürgen F.Brune Muhammad Usman Khan University of Engineering and Technology lahore Lahore 54890Pakistan Colorado school of Mines GoldenCO 80401USA

Gob ventilation boreholes(GVBs)are widely used for degasification in *** coal *** on geological conditions,30–50%of methane can be recovered from longwall gob using GVBs.A NIOSH funded research at the Colorado school of Mines confirmed that GVBs can efficiently reduce methane at the ***,GVBs can also draw some fresh air from the face and create explosive gas zones(EGZs).Explosive gas mixtures may be formed in gob areas due to the increased ingress of oxygen from *** is critical to identify the locations for GVBs for maximizing extraction of methane and minimizing hazards of *** study analyzes the effect of operating parameters and design of GVB on methane extraction,EGZs formation,and face and tailgate methane *** extraction,formation of EGZs,and concentration of methane in working areas are significantly impacted by various *** factors include the distance of work face and tailgate from GVBs,diameter of GVBs,vacuum pressure of wellhead,GVB distance from the roof of the coal seam,and number of operating GVBs in a *** fluid dynamics(CFD)evaluations suggest optimal design and operating parameters of GVBs that can contribute to maximum benefits with minimum risks.

关键词： Longwall mining Explosive gas zones Computational fluid dynamics Gob ventilation boreholes

维普期刊数据库

A note on the unsteady flow of a fractional Maxwell fluid through a circular cylinder

在线全文

学校读者我要写书评

暂无评论

Acta Mechanica Sinica 2012年第2期28卷 308-314页

作者： M.Athar A.U.Awan Corina Fetecau Abdus Salam school of Mathematical Sciences GC University Lahore68-BNew Muslim Town LahorePakistan

In this note the velocity field and the adequate shear stress corresponding to the unsteady flow of a frac- tional Maxwell fluid due to a constantly accelerating circular cylinder have been determined by means of the Laplace and finite Hankel transforms. The obtained solutions satisfy all imposed initial and boundary conditions. They can easily be reduced to give similar solutions for ordinary Maxwell and Newtonian fluids. Finally, the influence of pertinent param- eters on the fluid motion, as well as a comparison between models, is underlined by graphical illustrations.

关键词： Fractional Maxwell fluid Velocity field Shear stress Exact solutions

维普期刊数据库

Impact of global financial crunch on financially innovative microfinance institutions in South Asia

在线全文

学校读者我要写书评

暂无评论

Financial Innovation 2018年第1期4卷 205-215页

作者： Faisal Mustafa Ambreen Khursheed Maham Fatima UCP business school Faculty of Management StudiesUniversity of Central PunjabLahorePakistan

The wave of global financial crises(2008-2009)caused a surge in the capital flows of developed countries particularly,between developed and developing *** crunch hit all financial sectors with unanticipated *** study evaluates the role of a country’s political practices in moderating the impact of global financial crunch on microfinance *** the fixed effect panel regression method on the dataset comprising of 95 MFIs operating in South Asia from 2003 to 2012,we determine that microfinance operational capability shares a positive relationship with the institutional attributes of a country and our output reveals that impact of country’s political practices is pervasive on the financial output of MFIs,liable to different levels of *** findings further reveals that MFIs situated in countries having vigorous political practices are less severely affected by the economic crunch.

关键词： Global financial crunch South Asia Microfinance institutions

Deep Learning-Based Robust DC Fault Protection Scheme for Meshed HVDC Grids

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

CSEE Journal of Power and Energy Systems 2023年第6期9卷 2423-2434页

作者： Muhammad Zain Yousaf Hui Liu Ali Raza Ali Mustafa the school of Electrical Engineering Guangxi UniversityNanning 530004China the school of Electrical Engineering University of LahoreLahore 39161Pakistan the school of Electrical Engineering Xi’an Jiaotong UniversityXi’an 710049China

Fast and reliable detection of faults is a significant technical challenge in transient-based protection for a modular multi-level converter(MMC)based high voltage direct current(HVDC)*** is because existing protection schemes rely heavily upon setting a complicated protective threshold,the failure of which causes high DC-fault currents in HVDC grids,and MMC is prone to such strong transient *** this context,this paper proposes a DC-line fault diagnosis technique based on a tuned long-short-term memory(LSTM)algorithm to improve the response and accuracy of transient-based *** discrete wavelet transform(DWT)extracts the transient features of DC-line voltages in the frequency-time *** healthy and faulty samples are incorporated during training even by considering the noise *** training,numerous test samples are run to evaluate the proposed algorithm’s robustness under various fault *** results show the proposed algorithm can detect DC faults and has a high recognition accuracy of 98.6%.Compared to contemporary techniques,it can perform well to identify DC-line faults because of the efficient training of characteristic features.

关键词： High voltage direct current(HVDC) longshort-term-memory(LSTM) primary protection voltage source converters(VSC)