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Urdu Ligature Recognition System:An Evolutionary Approach

Computers, Materials & Continua 2021年第2期66卷 1347-1367页

作者： naila habib khan Awais Adnan AbdulWaheed Mahdi Zareei Abdallah Aldosary Ehab Mahmoud Mohamed Department of Computer Science Institute of Management SciencesPeshawar25000Pakistan Department of Information Technology Hazara UniversityMansehra21120Pakistan School of Electrical and Computer Engineering Seoul National UniversitySeoul08826South Korea Tecnologico de Monterrey School of Engineering and SciencesZapopan45201Mexico Department of Computer Science Prince Sattam Bin Abdulaziz UniversityAs Sulayyil11991Saudi Arabia Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Electrical Engineering Department Faculty of EngineeringAswan UniversityAswan81542Egypt

Cursive text recognition of Arabic script-based languages like Urdu is extremely complicated due to its diverse and complex *** approaches like genetic algorithms have been used in the past for various optimization as well as pattern recognition tasks,reporting exceptional *** proposed Urdu ligature recognition system uses a genetic algorithm for optimization and *** the proposed recognition system observes the processes of pre-processing,segmentation,feature extraction,hierarchical clustering,classification rules and genetic algorithm optimization and *** pre-processing stage removes noise from the sentence images,whereas,in segmentation,the sentences are segmented into ligature *** features are extracted from each of the segmented ligature ***-feature hierarchical clustering is observed that results in clustered ***,classification rules are used for the representation of the clustered *** genetic algorithm performs an optimization mechanism using multi-level sorting of the clustered data for improving the classification rules used for recognition of Urdu *** conducted on the benchmark UPTI dataset for the proposed Urdu ligature recognition system yields promising results,achieving a recognition rate of 96.72%.

关键词： Classification rules genetic algorithm intra-feature hierarchical clustering ligature recognition Urdu script

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Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

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Computers, Materials & Continua 2021年第1期66卷 359-372页

作者： Abdul Waheed naila habib khan Mahdi Zareei Shahab Ul Islam Latif Jan Arif Iqbal Umar Ehab Mahmoud Mohamed Department of Information Technology Hazara UniversityMansehra21120Pakistan School of Electrical and Computer Engineering Seoul National UniversitySeoul08826Korea Department of Computer Science Institute of Management SciencesPeshawar25000Pakistan Tecnologico de Monterrey School of Engineering and SciencesZapopan45201Mexico Department of Computer Science IQRA National UniversityPeshawar25124Pakistan Department of Electrical Engineering University of Engineering TechnologyPeshawar25120Pakistan Electrical Engineering Department College of EngineeringPrince Sattam Bin Abdulaziz UniversityWadi Addwasir11991Saudi Arabia Electrical Engineering Department Faculty of EngineeringAswan UniversityAswan81542Egypt

Congestion control is one of the main obstacles in cyberspace *** in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet *** the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the *** tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic *** validity of the proposed model is checked through extensive simulation-based *** analysis is observed for different functions on internet *** performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue *** sets of experiments are observed with varying simulation *** experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

关键词： Random early detection(RED) active queue management(AQM) quality of service(QOS) throughput

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