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Reinforcement Learning-Based Optimization for Drone Mobility in 5G and Beyond Ultra-Dense Networks

Computers, Materials & Continua 2021年第9期68卷 3807-3823页

作者： jawad tanveer Amir Haider Rashid Ali Ajung Kim School of Optical Engineering Sejong UniversitySeoul05006Korea School of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea

Drone applications in 5th generation(5G)networks mainly focus on services and use cases such as providing connectivity during crowded events,human-instigated disasters,unmanned aerial vehicle traffic management,internet of things in the sky,and situation awareness.4G and 5G cellular networks face various challenges to ensure dynamic control and safe mobility of the drone when it is tasked with delivering these *** drone can fly in three-dimensional *** drone connectivity can suffer from increased handover cost due to several reasons,including variations in the received signal strength indicator,co-channel interference offered to the drone by neighboring cells,and abrupt drop in lobe edge signals due to antenna *** baseline greedy handover algorithm only ensures the strongest connection between the drone and small cells so that the drone may experience several *** for fast environment learning,machine learning techniques such as Q-learning help the drone fly with minimum handover cost along with robust *** this study,we propose a Q-learning-based approach evaluated in three different *** handover decision is optimized gradually using Q-learning to provide efficient mobility support with high data rate in time-sensitive applications,tactile internet,and haptics *** results demonstrate that the proposed algorithm can effectively minimize the handover cost in a learning *** work presents a notable contribution to determine the optimal route of drones for researchers who are exploring UAV use cases in cellular networks where a large testing site comprised of several cells with multiple UAVs is under consideration.

关键词： 5G dense network small cells mobility management reinforcement learning performance evaluation handover management

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Financial inclusion and carbon emissions in Asia:Implications for environmental sustainability

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Economic and Political Studies 2024年第1期12卷 88-104页

作者： Shahzad Hussain tanveer Ahmad Sabeeh Ullah Ajid Ur Rehmand Syed jawad Hussain Shahzad Department of Business Administration Rawalpindi Women UniversityRawalpindiPakistan Institute of Business Studies Kohat University of Science and TechnologyKohatPakistan Institute of Business and Management Sciences Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan NUST Business School National University of Sciences and TechnologyIslamabadPakistan Finance Control and Law DepartmentMontpellier Business SchoolMontpellierFrance

This study explores how carbon emissions are affected by financial *** a balanced panel data set of 26 Asian countries,we compute a composite index,through the principal component analysis(PCA)technique,of financial inclusion based on a set of attributes related to financial *** main analysis also delineates the subsamples of developed and developing Asian *** results reveal a long(short)-run positive(negative)impact of financial inclusion on carbon emissions across the Asian *** finding is also true for the developed country subsample,implying nonlinearity in shortand long-run *** the developing countries,a more pronounced long-run positive impact compared to developed countries is ***,the pairwise causality test results indicate the existence of bi-directional causality between financial inclusion and carbon *** findings have important policy implications,especially in the context of the strategic integration of financial inclusion and climate change strategies.

关键词： Financial inclusion CO2 emissions climate change sustainable development Asian countries

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A Hybrid Method for Edge Continuity Based on Pixel Neighbors Pattern Analysis (PNPA) for Remote Sensing Satellite Images

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International Journal of Communications, Network and System Sciences 2012年第9期5卷 624-630页

作者： Waqas Haider Muhammad Sharif Malik Mudassar Raza Abdul Wahab Izhar Ahmed Khan Umar Zia jawad tanveer Hadia Bashir Department of Computer Science COMSATS Institute of Information Technology Wah Cantt and Vehari Campus Pakistan

Edge enhancement is derived from lack of accurate result from edge detection techniques. The image which is captured from long distances carries a lot of noise and blur which causes edge discontinuity. Although some novel algorithms which are based on cellular neural network, fuzzy enhancement and binary morphology have shown accuracy in order to obtain refined edge but still the problem of edge discontinuity arises. Eliminating discontinuity of edge a hybrid technique is proposed based on pixel neighbors pattern analysis PNPA. In the technique Canny operator for initial edge detection, PNPA operation for edge enhancement are performed for remote sensing satellite image successively. The visual and subjective evaluation shows that the proposed PNPA operation can effectively eliminate the influence of edge discontinuity which occurred due to noise and blurr in original captured image, as comparing to existing edge segmenting processes.

关键词： Edge Detection Edge Enhancement

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