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A new controller for energy management system of EV
Shujaat Husain,Haroon Ashfaq,Mohammad Asjad Techno-Press 2022 Advances in energy research Vol.8 No.3
Recent concerns about rising fuel prices and greenhouse gas emissions have focused attention on alternative energy sources, particularly in the transport sector. Transportation consumes 40% of overall fuel usage. As a result, a growing majority of researches on Electric Vehicles (EVs) and their Energy Management Systems (EMS) have been done. In order to enhance the performance and to meet the needs of drivers, more information regarding the EMS is needed. A new Energy Management System is proposed using a FOPID controller. To put the concept into practice, state equations are utilised. The fifth-order state-space model under study is a linked model with several inputs and outputs and the transfer matrices are calculated for decoupling the system. Utilizing these transfer matrices to decouple the system and FOPID controller is used to tune the system. The tuned parameters are minimized using a Particle Swarm Optimization (PSO) approach with Integral Time Absolute Error (ITAE) as the goal. When the suggested FOPID system's results are compared to those of PID-controlled systems, a sizable improvement is observed, which is explained by the results.
Shujaat Ali,Abdul Rehman Umar,Kashif Hussain,Haji Muhammad,Muddasir Hanif,Mouna Hind Laiche,Sufian Rasheed,Kousar Yasmeen,Abdul Hameed,Muhammad Raza Shah 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.125 No.-
It’s crucial to develop cost-effective, rapid & reliable detection methods of specific analytes through sensorsuseful in the analytical and medicinal chemistry. We report a highly sensitive and selective colorimetricmethod for the detection of clonazepam by the new composite sensor DH-1,6-NAPY-8-CNAgNPscontaining 5-amino-7-(4-benzylpiperazin-1-yl)-2,4-bis(4-bromophenyl)-2-methyl-1,3-dihydro-1,6-naphthyridine-8-carbonitrile capped silver nanoparticles (AgNPs). The detection mechanism is basedon the H-bonding interactions between clonazepam and the sensor, that caused the aggregation of NPsthat initiated a sharp color change from yellow to red. The linear relationship between the adjacentabsorbance values (DA) vs. clonazepam concentration (range = 0.05–75 lM) showed a correlation coefficientof 0.9927. The limit of detection (LOD) was 3 nM, that is very significant achievement over theexisting reports. The proposed sensor is highly selective, with no interference from many other possibleinterfering substances. The sensor was successfully applied to the aqueous and human plasma samples,therefore DH-1,6-NAPY-8-CN-AgNPs demonstrated great potential for the on-site and real-time screeningof Clonazepam.
수잣후세인 ( Shujaat Hussain ),무하마드비랄아민 ( Muhammad Bilal Amin ),( Mahmood Ahmad ),이승룡 ( Sungyoung Lee ),정태충 ( Tae Choong Chung ) 한국정보처리학회 2013 한국정보처리학회 학술대회논문집 Vol.20 No.1
Smart home is one of the emerging domains to come up after advances in home appliances and automation technologies. There are many commercial solutions for smart homes yet many of them have yet to truly exploit the potential of private cloud for low level contextual services and ability to migrate to public cloud for more processing and storage. We propose a private cloud gateway for smart home which will have the ability to sense the new devices, ability to detect context of the situation and act in an appropriate way. It will also record the user logs which will be audited for improvement of the overall system.
ON GENERALIZATION OF BI-PSEUDO-STARLIKE FUNCTIONS
SHAH, SHUJAAT ALI,NOOR, KHALIDA INAYAT The Korean Society for Computational and Applied M 2022 Journal of applied mathematics & informatics Vol.40 No.1-2
We introduce certain subclasses of bi-univalent functions related to the strongly Janowski functions and discuss the Taylor-Maclaurin coefficients |a<sub>2</sub>| and |a<sub>3</sub>| for the newly defined classes. Also, we deduce certain new results and known results as special cases of our investigation.
HM-Prom: CNN based Prediction of TATA Promoters from Human and Mouse Sequences
Muhammad Shujaat,Kil To Chong 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
A promoter is a DNA element that is found surrounding the transcription start site and can regulate gene transcription. The detection of promoters is critical in defining transcription units, examining gene structure, assessing gene regulatory mechanisms, and annotating gene functional information. Many methods for predicting promoters have previously been proposed. However, these approaches’ performance still has to be improved. In this paper, we present HM-Prom, a strong deep learning model for analysing the properties of short eukaryotic promoter sequences and properly recognizing human and mouse promoter sequences. We performed experiments on a benchmark dataset and compared our results to four cutting-edge tools to demonstrate our superiority in 5-fold cross-validation. Furthermore, we put our classifier through its paces on an independent test dataset. Comparative results show that our method outperforms other approaches for recognizing promoters.