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Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed

Computers, Materials & Continua 2023年第6期75卷 6375-6393页

作者： Neelam Mughees mujtaba hussain Jaffery Abdullah Mughees Anam Mughees Krzysztof Ejsmont Department of Electrical and Computer Engineering COMSATS University IslamabadLahore Campus45550Pakistan School of Engineering and Technology National Textile UniversityFaisalabad37610Pakistan Department of Electrical Engineering Information Technology UniversityLahore54000Pakistan Department of Electrical Engineering GC UniversityFaisalabad38000Pakistan Faculty of Mechanical and Industrial Engineering Warsaw University of Technology02-524WarsawPoland

Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by ***,they are exceedingly unpredictable since they rely highly on weather and atmospheric *** microgrids,smart energy management systems,such as integrated demand response programs,are permanently established on a step-ahead basis,which means that accu-rate forecasting of wind speed and solar irradiance intervals is becoming increasingly crucial to the optimal operation and planning of *** this in mind,a novel“bidirectional long short-term memory network”(Bi-LSTM)-based,deep stacked,sequence-to-sequence autoencoder(S2SAE)forecasting model for predicting short-term solar irradiation and wind speed was developed and evaluated in *** create a deep stacked S2SAE prediction model,a deep Bi-LSTM-based encoder and decoder are stacked on top of one another to reduce the dimension of the input sequence,extract its features,and then reconstruct it to produce the *** of the proposed deep stacked S2SAE forecasting model were optimized using the Bayesian optimization ***,the forecasting performance of the proposed Bi-LSTM-based deep stacked S2SAE model was compared to three other deep,and shallow stacked S2SAEs,i.e.,the LSTM-based deep stacked S2SAE model,gated recurrent unit-based deep stacked S2SAE model,and Bi-LSTM-based shallow stacked S2SAE *** these models were also optimized and modeled in *** results simulated based on actual data confirmed that the proposed model outperformed the alternatives by achieving an accuracy of up to 99.7%,which evidenced the high reliability of the proposed forecasting.

关键词： Deep stacked autoencoder sequence to sequence autoencoder bidirectional long short-term memory network wind speed forecasting solar irradiation forecasting

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Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

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Computers, Materials & Continua 2022年第6期71卷 4275-4293页

作者： Waleed Rafique Ayesha Khan Ahmad Almogren Jehangir Arshad Adnan Yousaf mujtaba hussain Jaffery Ateeq Ur Rehman Muhammad Shafiq Department of Electrical&Computer Engineering COMSATS University Islamabad Lahore CampusLahore54000Pakistan Syed Babar Ali School of Science and Engineering Lahore University of Management SciencesLahore54000Pakistan Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11633Saudi Arabia Department of Electrical Engineering Superior UniversityLahore54000Pakistan Department of Electrical Engineering Government College UniversityLahore54000Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system *** this research,a novel control techniquebased Hybrid-Active Power-Filter(HAPF)is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor(PF)and Total–Hormonic Distortion(THD)and the performance of a *** work proposed a soft-computing technique based on Particle Swarm-Optimization(PSO)and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control ***,the control algorithms are implemented for an instantaneous reactive and active current(Id-Iq)and power theory(Pq0)in *** prevent the degradation effect of disturbances on the system’s performance,PS0-PI is applied in the inner loop which generate a required dc ***,a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load *** presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the ***,the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller(FLC)are optimal that will detect reactive power and harmonics much faster and *** proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI(Voltage Source Inverter),and thus the simulation has been taken in SIMULINK/*** proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics *** a result of the comparison,it can be concluded that the PSO-basedAdaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.

关键词： Harmonics compensation soft computing technique hybrid fuzzy PSO based PI controller HSAPF power quality

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Deep Deterministic Policy Gradient to Regulate Feedback Control Systems Using Reinforcement Learning

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Computers, Materials & Continua 2022年第4期71卷 1153-1169页

作者： Jehangir Arshad Ayesha Khan Mariam Aftab mujtaba hussain Ateeq Ur Rehman Shafiq Ahmad Adel M.Al-Shayea Muhammad Shafiq Department of Electrical&Computer Engineering COMSATS University IslamabadLahore Campus54000Pakistan Department of Electrical Engineering Government College UniversityLahore54000Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Controlling feedback control systems in continuous action spaces has always been a challenging ***,reinforcement learning is mainly an area of artificial intelligence(AI)because it has been used in process control for more than a ***,the existing algorithms are unable to provide satisfactory ***,this research uses a reinforcement learning(RL)algorithm to manage the control *** propose an adaptive speed control of the motor system based on depth deterministic strategy gradient(DDPG).The actor-critic scenario using DDPG is implemented to build the RL *** addition,a framework has been created for traditional feedback control systems to make RL implementation easier for control *** RL algorithms are robust and proficient in using trial and error to search for the best *** proposed algorithm is a deep deterministic policy gradient,in which a large amount of training data trains the *** the system is trained,the agent can automatically adjust the control *** algorithm has been developed using Python 3.6 and the simulation results are evaluated in the MATLAB/Simulink *** performance of the proposed RL algorithm is compared with a proportional integral derivative(PID)controller and a linear quadratic regulator(LQR)*** simulation results of the proposed scheme are promising for the feedback control problems.

关键词： Feedback control systems reinforcement learning artificial intelligence

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Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms

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Computers, Materials & Continua 2023年第11期77卷 1795-1814页

作者： Arsal Javaid Areeb Abbas Jehangir Arshad Mohammad Khalid Imam Rahmani Sohaib Tahir Chauhdary mujtaba hussain Jaffery Abdulbasid S.Banga Department of Electrical and Computer Engineering COMSATS University IslamabadLahore CampusLahore54000Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia Department of Electrical and Computer Engineering College of EngineeringDhofar UniversitySalalah211Oman

To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this *** addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine *** novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on ***,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted *** proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in *** results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing *** proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture.

关键词： Posture detection FSR sensor machine learning real-time KNN

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Pharmacokinetics/Pharmacodynamics study of Fixtral SB as compared to supra bioavailable itraconazole and conventional itraconazole

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World Journal of Pharmacology 2023年第1期12卷 1-11页

作者： Syed mujtaba hussain Naqvi Monil Yogesh Neena Gala Snehal Muchhala Anand Arumugam Dhananjay Panigrahi Dipak Patil Rahul Rathod Amey Mane Medical Affairs Dr Reddy’s LaboratoriesHyderabad 500016India Global Clinical Management Dr Reddy’s LaboratoriesHyderabad 500016India Formulation Development Dr Reddy’s LaboratoriesHyderabad 500016India

BACKGROUND Itraconazole is a broad-spectrum triazole antifungal inhibiting fungal growth by inhibiting ergosterol synthesis and exhibits a nonlinear pharmacokinetic *** absorption pattern with wide fluctuations in blood levels causes inconsistent and unpredictable clinical behaviour of this drug despite its low minimum inhibitory concentration(MIC)as compared to other antifungal *** To compare the oral bioavailability and bioequivalence of Fixtral SB(supra bioavailable itraconazole)with reference product R2(supra bioavailable 2×50 mg itraconazole).METHODS The study population consisted of 54 healthy volunteers,aged between 18-45 years and randomized to receive a single oral dose of either test[T;Fixtral SB(supra bioavailable itraconazole)100 mg]or reference product(R1;Sporanox 100 mg×2 capsules and R2;Lozanoc capsules 50 mg×2 capsules).Blood samples were taken pre-dose and post-dose up to 96 *** study evaluated bioequivalence by comparing the oral bioavailability of the test product with reference product *** pharmacodynamic characteristics of the drug were evaluated by comparing the test product with reference product ***(PK)-PD comparative analysis[area under the concentration-time curve(AUC)/minimum inhibitory concentration(MIC)>25]was performed for conventional itraconazole 100 mg and supra bioavailable itraconazole 50 *** events(AEs)assessments were performed in each study period and post-study *** Statistical analysis of primary PK variables revealed bioequivalence,with confidence intervals being completely inside the acceptance criteria of 80%-125%.The peak concentration levels of itraconazole were achieved at 10 h(T)and 8.5 h(R2),*** parameter assessment showed that AUC/MIC for R1 are comparable to Fixtral SB 100mg for MIC levels up to 16mcg/mL(P>0.05 and observed P=0.3196).Six AEs were observed that were mild to moderate in severity and *** severe AE was reported.

关键词： Supra-Bioavailable itraconazole Conventional itraconazole Oral bioavailability Pharmacodynamics Efficacy Adverse events

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Multi-Modality and Feature Fusion-Based COVID-19 Detection Through Long Short-Term Memory

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Computers, Materials & Continua 2022年第9期72卷 4357-4374页

作者： Noureen Fatima Rashid Jahangir Ghulam mujtaba Adnan Akhunzada Zahid hussain Shaikh Faiza Qureshi Center of Excellence for Robotics Artificial Intelligenceand BlockchainDepartment of Computer ScienceSukkur IBA UniversitySukkurPakistan Department of Computer Science COMSATS University Islamabad–Vehari CampusPakistan Faculty of Computing and Informatics University Malaysia SabahKota Kinabalu88400Malaysia Department of Mathematics Sukkur IBA UniversitySukkurPakistan

The Coronavirus Disease 2019(COVID-19)pandemic poses the worldwide challenges surpassing the boundaries of country,religion,race,and *** current benchmark method for the detection of COVID-19 is the reverse transcription polymerase chain reaction(RT-PCR)***,this testing method is accurate enough for the diagnosis of ***,it is time-consuming,expensive,expert-dependent,and violates social *** this paper,this research proposed an effective multimodality-based and feature fusion-based(MMFF)COVID-19 detection technique through deep neural *** multi-modality,we have utilized the cough samples,breathe samples and sound samples of healthy as well as COVID-19 patients from publicly available COSWARA *** set of experimental analyses were performed to evaluate the performance of our proposed *** useful features were extracted from the aforementioned modalities that were then fed as an input to long short-term memory recurrent neural network algorithms for the classification *** set of experimental analyses were performed to evaluate the performance of our proposed *** experimental results showed that our proposed approach outperformed compared to four baseline approaches published *** believe that our proposed technique will assists potential users to diagnose the COVID-19 without the intervention of any expert in minimum amount of time.

关键词： Covid-19 detection long short-term memory feature fusion deep learning audio classification

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Pneumomediastinum, pneumorachis, subcutaneous emphysema: An unusual complication of leukemia in a child

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World Journal of Clinical Cases 2013年第7期1卷 224-226页

作者： Hakim Irfan Showkat Aleem Jan Arif hussain Sarmast Gull Mohammad Bhat Basharat mujtaba Jan Yasir Bashir Department of Internal Medicine Sheri-Kashmir Institute of Medical Sciences

Pneumorrhachis(PR), or epidural emphysema, denotes the presence of air in the spinal epidural space. It can be associated with a variety of etiologies, including trauma; recent iatrogenic manipulations during surgical, anesthesiological and diagnostic interventions;malignancy and its associated therapy. It usually represents an asymptomatic epiphenomenon but also can be symptomatic by itself, as well as by its underlying pathology, and rarely can be fatal. The pathogenesis and etiology of PR are varied and can sometimes be a diagnostic challenge. As such, there are no standard guidelines for the management of symptomatic PR and its treatment is often individualized. Here, we present a case of a 14-year-old boy treated for leukemia who developed this complication and whether chemotherapy related or not, it proved to be fatal for him. To our knowledge, this is the first case in the literature of this complication with acute lymphoblastic leukemia.

关键词： Pneumomediastinum Leukemia Pneumorachis Subcutaneous emphysema Chemotherapy

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