Habib Ullah Manzoor

Scopus Publications

Remaining Useful Life (RUL) Prediction Methods for Machine Health Estimation and Fault Diagnosis: A Comprehensive Review of Latest Techniques and Future Prospects
Arslan Ahmed Amin, Ansa Mubarak, Saba Waseem, Zuhair A. Alqarni, Habib Ullah Manzoor
Engineering Reports, 2026
This paper aims to provide a state‐of‐the‐art review of the most recent Remaining Useful Life (RUL) prediction methods, starting from statistical methods, machine learning (ML), deep learning (DL), and their ensemble methods. The limitations and strengths of the earlier techniques, data‐driven techniques, and combined model‐based and data‐driven solutions were discussed. The study focuses on RUL estimates in preventive maintenance policies in different industrial fields where failure prediction and maintenance plans are crucial. While model‐based methods provide high accuracy, they are highly dependent on system knowledge and are likely to be restricted by more comprehensive datasets and various types of degradation features. In contrast, data‐driven methods are becoming more popular and flexible in solving large‐scale problems and complicated degradation features. The paper also highlights the importance of different AI learning models for achieving higher accuracy in predictions, with dependency on the time aspect and hierarchical feature space. Both hybrid and ensemble methods are discussed to have promising applications in integrating the advantages of model‐based and data‐driven approaches to improve prediction reliability. Real‐life examples and applications are described to demonstrate how RUL prediction can help in increasing performance and decreasing expenses. Finally, future research directions for further work are identified to address these challenges.
Simulation and Modeling Techniques for Multi-Objective Optimization of Hybrid Fast EV Charging Station
Sana Sultan, Fawad Azeem, Habib Ullah Manzoor, Ghous Bakhsh Narejo, Tareq Manzoor
Battery Energy, 2026
In this era, electric vehicles (EVs) have become widely popular in the transportation sector because of their smaller carbon footprint and less noise. The charging stations for EVs are rapidly increasing to meet their charging demands in a shorter time. The hybrid charging stations, combined with renewable sources like solar and wind energy, offer an environmentally friendly solution for the massive adoption of EVs. However, the additional load of EV charging stresses the utility grid, and the intermittency of these renewable sources adds uncertainty to the performance of charging stations. The load management of the EVCS faces challenges during the unavailability of renewable energy and peak demand hours. This research focuses on the demand side management of the EV load through a coordinated demand response strategy that effectively schedules the EVs and employs a multi‐objective optimization technique to balance operational cost and Loss of Power Supply Probability (LPSP) of the charging station. Three commonly used optimization algorithms, namely Multi‐Objective Particle Swarm Optimization (MOPSO), Multi‐Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) and Non‐dominated Sorting Genetic Algorithm (NSGA‐II), are analyzed for a hybrid fast EVCS to determine an optimal trade‐off solution that can improve economic feasibility and reliability. Sensitivity analysis of these techniques is performed to analyse the solution of each algorithm under perturbations.
Trustworthy Distributed Load Forecasting in Resource-Limited Smart Grids and Buildings via Random Layer Aggregation
Habib Ullah Manzoor, Attia Shabbir, Rao Naveed Bin Rais, Sajjad Hussain, Ahmed Zoha
International Journal of Intelligent Systems, 2026
Federated learning (FL) is a privacy‐preserving method for short‐term load forecasting in energy networks. However, current defense mechanisms against adversarial attacks often depend on supplementary machine learning frameworks, such as anomaly detection models or Byzantine‐robust aggregators. These frameworks add significant computational overhead, straining edge devices such as smart meters and IoT systems with limited processing power. To solve this issue, we propose a new defense‐free framework called federated random layer aggregation (FedRLA). By aggregating only one randomly chosen neural network layer per communication round, FedRLA limits adversarial influence to isolated layers. This reduces attack surfaces by 66% compared to full‐model aggregation (FedAvg). Using 8‐bit quantization, FedRLA cuts data transmission by 92.97% without accuracy loss (MAE: 0.08 kWh vs. FedAvg’s 0.076 kWh). Under four model poisoning attacks, it reduces forecasting errors by 19%–35% compared to FedAvg. FedRLA also uses 24% less CPU and 13% less memory than frameworks such as FedProx, while training 58% faster. It combines communication efficiency (0.195 MB/round), adversarial robustness (MAE ≤ 0.11 kWh under ϵ = 0.2 DP), and low resource consumption, offering a scalable solution for secure FL in resource‐constrained energy networks.
Enhancing group-based emotional intelligence in children through an adaptive activity system driven by artificial intelligence
Heena Irfan, Awais Hassan, Talha Waheed, Habib Ullah Manzoor, Iram Aziz
Peerj Computer Science, 2026
Emotional intelligence (EI) is a crucial skill set because it impacts the social interactions, decision making ability and general well-being of the kids. This study focuses on the creation of adaptive activity generator which aims to improve the emotional intelligence of kids between the ages of 4 to 12 years. The responses from Strengths and Difficulties Questionnaire (SDQ) are used to identify the weak emotional intelligence dimensions. In order to dynamically create customized activities that are according to the child’s developmental stage and particular EI problems, it makes use of a Large Language Model (LLM). The system also forms groups of children who share the same weak emotional intelligence (EI) dimension and belong to the same age group, in order to promote collaborative learning and teamwork. Activities are divided into three difficulty levels (low, medium, and high) and focus on specific emotional intelligence (EI) skills, such as self-awareness, empathy, motivation, self-regulation, and social skills. Using hierarchical clustering, clustering analysis produced four unique groupings based on similar behavioral and emotional traits. Most participants showed overall improvement, while a smaller group required further development in certain EI dimensions. The results suggest that the adaptive activity generator is an effective tool for enhancing emotional intelligence in children. A paired T-test confirmed a statistically significant decrease in weak dimensions after the intervention demonstrating the effectiveness of the adaptive activity generator. This approach seeks to fill gaps in current educational practices by offering parents, teachers, and psychologists a scalable and interactive way to support children’s emotional development.
Evaluation of Electric Vehicle Retrofitting Challenges Through a Design, Operation, and Charging Infrastructure Assessment Framework
Hasan A. Zidan, Habib Ullah Manzoor, Fawad Azeem, Tareq Manzoor
Energy Science and Engineering, 2025
Electric vehicle (EV) is a resurging technology with a promising future. However, range anxiety and lack of charging infrastructure remain challenges for the mass‐scale adoption of EVs. Nevertheless, with technological advancements and rapid development of charging infrastructure, EV adoption has increased massively. On the one hand, the adoption of modern EVs has dramatically increased. On the other hand, retrofitting of conventional vehicles to EVs has significantly gained attention, especially in developing countries. One of the alarming concerns related to retrofitting is less awareness related to the retrofitting challenges that may raise safety issues along with the range anxiety. This research project identifies the challenges of retrofitting conventional gasoline engines to EVs while assessing battery bank capacity, drive train motor performance, and charging impact. A three‐wheel gasoline vehicle is converted into an EV to identify design, operational, and mass‐scale charging impacts. A three‐wheeled petrol‐engine vehicle was selected for the conversion. The geographic location of Karachi Pakistan was selected for testing the retrofitted vehicle. In the first phase, a simulation study is conducted using drive train simulation software for the selection of the electric motor and the sizing of the battery bank. In the second phase, the converted vehicle is tested on the road to analyze operational characteristics, that is, battery drain time, speed, and performance of the traction motor. In the third phase, mass‐scale charging power requirements are quantified. The results revealed that conventional car transformation into an EV can pose challenges in all three phases, that is, design, operation, and mass‐scale charging. It was analyzed that a low space constraint for the battery reduces the battery bank, eventually restricting the vehicle operation to only 15–32 min with a speed of 10 and 20 km/h. On the other hand, with the higher mass vehicles charging, the total power required is 125 kW with a 0.7 demand factor, whereas 117 kW of charging is required in the nighttime during peak hours, which can put a load on the grid with the increasing number of vehicles and less travel time.
Smart grid security through fusion-enhanced federated learning against adversarial attacks
Attia Shabbir, Habib Ullah Manzoor, Ahmed Zoha, Zahid Halim
Engineering Applications of Artificial Intelligence, 2025
Swarm-Optimized ZnO/CdS/CIGS/GaAs Solar Cell for Enhanced Efficiency and Thermal Resilience
Habib Ullah Manzoor, Tareq Manzoor, Sajjad Hussain, Muhammad Nasir Manzoor, Ahmed Zoha
Advanced Energy and Sustainability Research, 2025
Optimizing solar cell design is vital for boosting efficiency, cutting production costs, and meeting the increasing demand for renewable energy solutions. Through meticulous adjustments in material compositions and device architectures, optimization enhances energy conversion efficiency, making solar power more competitive and adaptable across various applications. This article presents the optimization and efficiency enhancement of a ZnO/CdS/CIGS solar cell with GaAs. The optimization process utilizes the particle swarm optimization algorithm with a step‐by‐step approach. Solar cells are designed using SCAPS‐1D software, and optimization is performed using Python. The optimized ZnO/CdS/CIGS solar cell achieves an efficiency of 32.4%, which rises to 44.7% upon integrating a GaAs layer. Further efficiency gains are observed, reaching 53.2% through back contact optimization, providing a power density of 54 mW cm−2. Optimization also notices a significant improvement in quantum efficiency. The cells are tested under concentrated solar irradiance (1000–10 000 W m−2) and temperatures (300–800 K). Results show that at 10 000 W m−2 and 800 K, the ZnO/CdS/CIGS/GaAs cell requires 53.9% less material than the ZnO/CdS/CIGS cell. Thus, adding GaAs enhances efficiency and thermal resilience, making it ideal for concentrated photovoltaics.
Investigation of Thermal Management Capacity of Casson Electrolytes in Porous Electrodes in Lithium-Ion Battery Applications
Tareq Manzoor, S. Iqbal, Tauseef Anwer, Sanaullah Manzoor, Ghulam Mustafa, Habib Ullah Manzoor
Battery Energy, 2025
The study of the Casson electrolyte in lithium‐ion batteries (LIBs) is important because of their complexities due to tougher operational conditions and other challenges during charging–discharging challenges with their improved thermal management capacity and enhanced safety. This further optimizes the thermal management avoiding chances of hot spots or thermal runaway, thereby making LIBs safer. In this investigation, convective loads for non‐Newtonian fluid as electrolyte Casson‐type boundary layer flow related to plate and flat surfaces in non‐Darcy permeable porous electrodes have been deliberated. We have employed the Optimal Homopotic Asymptotic Method technique to solve the equation of the system. The effects and influences of Casson factors, permeability, flow constraints, Prandtl values related to flow and thermal dissipation, and boundary layer profiles have been studied. From the results, it is concluded that thermal parameters and porousness have affected the system, and the upsurge in the porousness actually decreases heat transport effects and proportions. The results of this study are relevant to the development of more effective porous electrodes for achieving high performance with long cycle life. These studies help improve the utilization of mass and heat transfer properties, as affected by the non‐Newtonian behavior of the electrolyte, to help in the design of next‐generation LIBs with higher energy density along with fast charge/discharge rates.
DC vs. AC distribution: Revealing the efficiency advantage of DC in today's energy landscape
Asfand Haroon, Hasan Erteza Gelani, Hira Tahir, Habib Ullah Manzoor
Plos One, 2025
The new millennium witnessed an unanticipated escalation in the installation of rooftop solar panels, particularly due to the development of highly efficient power electronic converters (PECs). The ‘battle of currents’ between AC and DC, which settled in the favor of AC in the nineteenth century, reignited as DC is striking back due to this technological augmentation. The shifting trend towards DC is more pronounced in the residential sector, which necessitates a comparative analysis of AC and DC at distribution scale on realistic grounds. Modern home data extracted from the energy information administration (EIA) has been utilized to devise a mathematical model based on bottom-up approach. The comparative analysis has been performed encompassing scenarios of varying PEC efficiencies as a result of daily load variation. Moreover, the scenarios of multiple PEC efficiencies and rooftop solar capacities are also considered. The comparative analysis revealed efficiency advantage of 1.966%, 1.41% and 1.17% in favor of DC as compared to AC for the scenarios considered. In the end future recommendations are presented to further enhance the efficiency of DC, thereby providing a concrete standing for power industry decision of adopting DC at distribution scale.
Optimized Control of Hybrid Energy Storage Systems Using Whale Optimization Algorithm for Enhanced Battery Longevity and Stability in Microgrids
Nouman Alam Siddiqui, Hira Tahir, Muhammad Akram, Habib Ullah Manzoor
Engineering Reports, 2025
The target of achieving net‐zero emissions by 2050 requires integrating a significant share of renewable energy. However, this integration can cause instability in microgrid operations. Hybrid energy storage systems (HESS), consisting of battery energy storage systems (BESS) and supercapacitors, address these challenges but necessitate complex control strategies. Traditional frequency‐based methods (FBM) enhance HESS performance but do not guarantee continuous operation and may lead to BESS degradation. This article proposes an optimized FBM control approach using the whale optimization algorithm (WOA) to improve HESS operation. The method optimizes two key variables: current sharing coefficients and the smoothing constant, enabling continuous HESS functionality. The proposed FBM‐WOA reduces high‐frequency current stress on BESS, minimizes BESS usage, and ensures supercapacitor state‐of‐charge levels remain within safe limits. The proposed approach achieves the lowest BESS life loss and voltage fluctuations in both test load and microgrid load cases. It decreases BESS life loss by 11.59% and 0.25% compared to rule‐based (FB‐RB) and current sharing coefficient (FB‐COEFF) methods, respectively, for test load cases. Similarly, it reduces average BESS life loss by 1.45% and 2.35% compared to FB‐RB and FB‐COEFF methods for real load cases over five different days.
Effect of Optimized Tilt Angle of PV Modules on Solar Irradiance for Residential and Commercial Buildings in Different Cities of Pakistan: Simulation-Based Study
Habib Ullah Manzoor, Sheikh Muhammad Aaqib, Tareq Manzoor, Fawad Azeem, Muhammad Waqas Ashraf, Sanaullah Manzoor
Energy Science and Engineering, 2025
Exploring the Potential of Cross-Border Energy Trade in SAARC Countries for Achieving Sustainable Development Goals (SDGs)
Hassan Zidan, Maaz Tahir Malik, Usman Rafique, Fawad Azeem, Tareq Manzoor, Habib Ullah Manzoor
Energy Science and Engineering, 2025
Integrated Fuzzy-Knapsack Based Demand Response Energy Management System for Smart Grid Buildings
Zulfiqar Memon, Fawad Azeem, Tareq Manzoor, Habib Ullah Manzoor
Energy Science and Engineering, 2025
Optimization of indium concentration and compositional grading in InGaN heterojunction solar cells by SCAPS-1D simulation
Mohammed Kakasur Omar, Habib Ullah Manzoor, Sha Shiong Ng, Mohd Marzaini Mohd Rashid, Mohd Zamir Pakhuruddin
Physica Scripta, 2025
Enhancing Consumer Privacy in Federated Load Forecasting Through Single-Layer Aggregation
Habib Ullah Manzoor, Muhammad Ali Jamshed, Ahmed Zoha, Sanaullah Manzoor
IEEE Consumer Electronics Magazine, 2025
Novel Stealth Communication Round Attack and Robust Incentivized Federated Averaging for Load Forecasting
Habib Ullah Manzoor, Kamran Arshad, Khaled Assaleh, Ahmed Zoha
IEEE Transactions on Sustainable Computing, 2025
Reliable Short-Term Load Forecasting using Robust Federated Split Learning Framework
Habib Ullah Manzoor, Ao Chen, Rao Naveed Bin Rais, Sajjad Hussain, Ahmed Zoha
2025 IEEE 10th Workshop on the Electronic Grid Egrid 2025 Proceedings, 2025
Hybrid Neuromorphic-Federated Learning for Activity Recognition Using Multi-modal Wearable Sensors
Multimodal Intelligent Sensing in Modern Applications, 2025
Semantic-Aware Federated Blockage Prediction (SFBP) in Vision-Aided Next-Generation Wireless Network
Ahsan Raza Khan, Habib Ullah Manzoor, Rao Naveed Bin Rais, Sajjad Hussain, Lina Mohjazi, Muhammad Ali Imran, Ahmed Zoha
IEEE Transactions on Network and Service Management, 2025
Adaptive Single-layer Aggregation Framework for Energy-efficient and Privacy-preserving Load Forecasting in Heterogeneous Federated Smart Grids
Habib Ullah Manzoor, Atif Jafri, Ahmed Zoha
Internet of Things the Netherlands, 2024
Centralised vs. decentralised federated load forecasting in smart buildings: Who holds the key to adversarial attack robustness?
Habib Ullah Manzoor, Sajjad Hussain, David Flynn, Ahmed Zoha
Energy and Buildings, 2024
Robustness Against Data Integrity Attacks in Decentralized Federated Load Forecasting
Attia Shabbir, Habib Ullah Manzoor, Muhmmand Naisr Manzoor, Sajjad Hussain, Ahmed Zoha
Electronics Switzerland, 2024
Evaluation of the potential power generation resources in SAARC region for sustainable energy trade
Usman Rafique, Hasan A. Zidan, Fawad Azeem, Sarang Amir, Tareq Manzoor, Habib Ullah Manzoor
Energy Science and Engineering, 2024
A Survey of Security Strategies in Federated Learning: Defending Models, Data, and Privacy
Habib Ullah Manzoor, Attia Shabbir, Ao Chen, David Flynn, Ahmed Zoha
Future Internet, 2024
Antimony Trisulfide with Graphene Oxide Coated Titania Nanotube Arrays as Anode Material for Lithium-ion Batteries
Tauseef Anwar, Tareq Manzoor, Naveed Hussain, Syed Nasir Shah, Shazia Perveen, Sana Ullah Asif, Farhat Nosheen, Abdul Jabbar Khan, Habib Ullah Manzoor
Journal of Inorganic and Organometallic Polymers and Materials, 2024
Computational Optimization for CdS/CIGS/GaAs Layered Solar Cell Architecture
Satyam Bhatti, Habib Ullah Manzoor, Ahmed Zoha, Rami Ghannam
Energies, 2024
Finite Element Approach for Rheological Behavior in Colloidal Electrolytes in Lithium-Ion Battery Performance
Ahsan Raza, Tareq Manzoor, Shaukat Iqbal, Tauseef Anwar, Adeel Ashraf, Habib Ullah Manzoor
ACS Omega, 2024
Leveraging InGaN solar cells for visible light communication reception
Habib Ullah Manzoor, Sanaullah Manzoor, Muhammad Ali Jamshed, Tareq Manzoor
Iet Networks, 2024
Magnetic micro-fluidics in 3D microchannel at the micro-scale: Unlocking nano-porous electrode potential for lithium-ion micro-batteries
Adeel Ashraf, Tareq Manzoor, Shaukat Iqbal, Tauseef Anwar, Muhammad Farooq‐i‐Azam, Zeashan Khan, Habib Ullah Manzoor
Energy Storage, 2024
Resilience of Federated Learning Against False Data Injection Attacks in Energy Forecasting
Attia Shabbir, Habib Ullah Manzoor, Ridha Alaa Ahmed, Zahid Halim
2024 International Conference on Green Energy Computing and Sustainable Technology Gecost 2024, 2024
Rethinking Federated Learning: An Adversarial Perspective on Global vs. Local Learning for Load Forecasting
Habib Ullah Manzoor, Attia Shabiar, Dinh C. Nguyen, Lina Mohjazi, Aryan Kaushik, Ahmed Zoha
2024 IEEE Conference on Standards for Communications and Networking Cscn 2024, 2024
A Privacy and Energy-Aware Federated Framework for Human Activity Recognition
Ahsan Raza Khan, Habib Ullah Manzoor, Fahad Ayaz, Muhammad Ali Imran, Ahmed Zoha
Sensors, 2023
Revolutionizing Low-Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques
Satyam Bhatti, Habib Ullah Manzoor, Bruno Michel, Ruy Sebastian Bonilla, Richard Abrams, Ahmed Zoha, Sajjad Hussain, Rami Ghannam
Advanced Energy and Sustainability Research, 2023
FedBranched: Leveraging Federated Learning for Anomaly-Aware Load Forecasting in Energy Networks
Habib Ullah Manzoor, Ahsan Raza Khan, David Flynn, Muhammad Mahtab Alam, Muhammad Akram, Muhammad Ali Imran, Ahmed Zoha
Sensors, 2023
Optimization of different TDM techniques in DWDM optical networks for FWM suppression
Alishah Khalid, Habib Ullah Manzoor, Hafiz Ashiq Hussian, Moustafa H. Aly
Optical and Quantum Electronics, 2023
Defending Federated Learning from Backdoor Attacks: Anomaly-Aware FedAVG with Layer-Based Aggregation
Habib Ullah Manzoor, Ahsan Raza Khan, Tahir Sher, Wasim Ahmad, Ahmed Zoha
IEEE International Symposium on Personal Indoor and Mobile Radio Communications PIMRC, 2023
Blockchain-Empowered Immutable and Reliable Delivery Service (BIRDS) Using UAV Networks
Sana Hafeez, Habib Ullah Manzoor, Lina Mohjazi, Ahmed Zoha, Muhammad Ali Imran, Yao Sun
IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks Camad, 2023
Numerical simulation of homojunction p-i-n In0.4Ga0.6N solar cell with different absorber layer configurations
A.K. Tan, H.U. Manzoor, N.A. Hamzah, M.A. Ahmad, S.S. Ng, Z. Hassan
Optik, 2022
Carrier Density and Thickness Optimization of InxGa1-xN Layer by Scaps-1D Simulation for High Efficiency III-V Solar Cell
Habib Ullah Manzoor, Aik Kwan Tan, Sha Shiong Ng, Zainuriah Hassan
Sains Malaysiana, 2022
Influence of corona discharge on the hydrophobic behaviour of nano/micro filler based silicone rubber insulators
M Hijaaj Tahir, A Arshad, Habib Ullah Manzoor
Materials Research Express, 2022
Fault Detection and Protection Methodologies for High Voltage AC Transmission Lines
Pakistan Journal of Engineering and Applied Sciences, 2022
FedClamp: An Algorithm for Identification of Anomalous Client in Federated Learning
Habib Ullah Manzoor, Muhammed Shahzeb Khan, Ahsan Raza Khan, Fahad Ayaz, David Flynn, Muhammad Ali Imran, Ahmed Zoha
Icecs 2022 29th IEEE International Conference on Electronics Circuits and Systems Proceedings, 2022
Performance Analysis of Magnetic Nanoparticles during Targeted Drug Delivery: Application of OHAM
Muhammad Zafar, Muhammad Saif Ullah, Tareq Manzoor, Muddassir Ali, Kashif Nazar, Shaukat Iqbal, Habib Ullah Manzoor, Rizwan Haider, Woo Young Kim
CMES Computer Modeling in Engineering and Sciences, 2022
Energy Management in an Agile Workspace using AI-driven Forecasting and Anomaly Detection
Habib Ullah Manzoor, Ahsan Raza Khan, Mohammad Al-Quraan, Lina Mohjazi, Ahmad Taha, Hasan Abbas, Sajjad Hussain, Muhammad Ali Imran, Ahmed Zoha
Proceedings 2022 IEEE 4th Global Power Energy and Communication Conference Gpecom 2022, 2022
High conversion and quantum efficiency indium-rich p-InGaN/p-InGaN/n-InGaN solar cell
H.U. Manzoor, M.A. Md Zawawi, M.Z. Pakhuruddin, S.S. Ng, Z. Hassan
Physica B Condensed Matter, 2021
Privacy Enhanced Speech Emotion Communication using Deep Learning Aided Edge Computing
Hafiz Shehbaz Ali, Fakhar ul Hassan, Siddique Latif, Habib Ullah Manzoor, Junaid Qadir
2021 IEEE International Conference on Communications Workshops Icc Workshops 2021 Proceedings, 2021
Theoretical investigation of unsteady MHD flow within non-stationary porous plates
Tareq Manzoor, K. Nazar, S. Iqbal, Habib Ullah Manzoor
Heliyon, 2021
Optimization of PV Modules through Tilt Angle in Different Cities of Punjab, Pakistan
Muhammad Waqas Ashraf, Sheikh Muhammad Aaqib, Habib Ullah Manzoor, Muhammad Waqar Asharaf, Tareq Manzor, Muzammal Hussain Sethi
Proceedings 2020 23rd IEEE International Multi Topic Conference Inmic 2020, 2020
Improved transmission length in the presences of ambient noise and scintillation effect using duobinary modulation in 40 Gbps free space optical channel
Habib Ullah Manzoor, Sanaullah Manzoor, Tareq Manzoor, Talha Khan, Ashiq Hussain
Microwave and Optical Technology Letters, 2020
An improved micro-thermo-mechanics model for shape memory alloys: Analysis and applications
Tareq Manzoor, Muhammad Zafar, Sanaullah Manzoor, Habib Ullah Manzoor, Muddassir Ali, Woo Young Kim
Materials Research Express, 2020
Improving FWM efficiency in bi-directional ultra DWDM-PON networking centered light source by using PMD emulator
Habib Ullah Manzoor, Muhammad Zafar, Sana Ullah Manzoor, Talha Khan, Songzuo Liu, Tareq Manzoor, Saqib Saleem, Woo Young Kim, Muddassir Ali
Results in Physics, 2020
Analysis of Multiple Surface Electromagnetic Waves on the Planner Interface of Hyperbolic Medium and Rugate Filter Having Sinusoidal Refractive Index Profile
Habib Ullah Manzoor, Tareq Manzoor, Masroor Hussain
Plasmonics, 2020
FWM Mitigation in DWDM Optical Networks
Habib Ullah Manzoor, Tareq Manzoor, Ashiq Hussain, Moustafa H. Aly
Journal of Physics Conference Series, 2020
Facile synthesis of CuxZn1−xFe2O4 nanoparticles and their thermo-physical properties evaluation
Tareq Manzoor, Tariq Javed, Ghulam Mustafa, Habib Ullah Manzoor Ahmed, Abdul Razzaq
Applied Physics A Materials Science and Processing, 2019
FWM Reduction Using Different Modulation Techniques and Optical Filters in DWDM Optical Communication Systems: A Comparative Study
Habib Ullah Manzoor, Tareq Manzoor, Ashiq Hussain, Moustafa H. Aly, Sanaullah Manzoor
Iranian Journal of Science and Technology Transactions of Electrical Engineering, 2019
Cost Optimization of off Grid Photovoltaic System by Increasing Conversion Efficiency
Zain Ul Abideen, Arooj Aslam, Habib Ullah Manzoor, Tareq Manzoor, Nouman Bashir
1st International Conference on Electrical Communication and Computer Engineering Icecce 2019, 2019
Techno-Economo-Environmental Viability Assessment of Grid-Connected Photovoltaic System-A Case for Different Cities of Pakistan
Rida Younis, Amina Iqbal, Umer Farooq, Awais Iqbal, Habib Ullah Manzoor, Amir Mehmood, Tareq Manzoor
4th International Conference on Power Generation Systems and Renewable Energy Technologies Pgsret 2018, 2019
Assessment of technology transfer from grid power to photovoltaic: An experimental case study for Pakistan
Umer Farooq, Habib Ullah, Aamir Mehmood, Awais Iqbal, Rida Younis, Amina Iqbal, Fan Yang, Muhammad Arshad, Nouman Faiz
International Journal of Advanced Computer Science and Applications, 2019
Analysis of Bloch Surface Waves at the Interface Between Two Semi-infinite Rugate Filters with Symmetric Refractive Index Profiles
Habibullah Manzoor, Tareq Manzoor, Saqib Saleem, Sanaullah Manzoor, Masroor Hussain
Plasmonics, 2018
Multiple Bloch surface waves in visible region of light at the interfaces between rugate filter/rugate filter and rugate filter/dielectric slab/rugate filter
Habib Ullah Manzoor, Tareq Manzoor, Masroor Hussain, Sanaullah Manzoor, Kashif Nazar
Journal of Optics United Kingdom, 2018
Multiple surface electromagnetic waves guided by the planar interface of a rugate filter and a hyperbolic columnar thin film
Habib Ullah Manzoor, Husnul Maab, Muhammad Faryad
Optik, 2017
A note on fractional order in thermo-elasticity of shape memory alloys’ dampers
Tareq Manzoor, Zaffar Mehmood, Manzoor A. Zahid, S. Tauseef Mohyud-Din, Habibullah Manzoor, Sadiq Hashmi
International Journal of Heat and Mass Transfer, 2017
Complete suppression of FWM in ultra dense WDM-PON optical networks using centralized light source
Habib Ullah Manzoor, Ashiq Hussain, Chong Xiu Yu, Tareq Manzoor
Journal of Nonlinear Optical Physics and Materials, 2015
Dyakonov-Tamm waves guided by the planar interface of a rugate filter and a columnar thin film
Husnul Maab, Habib Ullah Manzoor, Muhammad Faryad
Journal of Electromagnetic Waves and Applications, 2015
Reduction of Four Wave Mixing by employing circular polarizers in DWDM optical networks
Habib Ullah Manzoor, Abaid Ullah Salfi, Tayyab Mehmood, Tareq Manzoor
Proceedings of 2015 12th International Bhurban Conference on Applied Sciences and Technology Ibcast 2015, 2015
Parametric analysis of four wave mixing in DWDM systems
Jameel Ahmed, Ashiq Hussain, M.Y. Siyal, Habibullah Manzoor, Abdullah Masood
Optik, 2014

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