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ORCIDMuhammad Asad 0003
Person information
- affiliation: National University of Sciences and Technology, School of Electrical Engineering and Computer Science, Islamabad, Pakistan
- affiliation: aeroLiFi GmbH, Wessling, Germany
- affiliation (2014 - 2019): Iqra University, Islamabad, Pakistan
Other persons with the same name
- Muhammad Asad — disambiguation page
- Muhammad Asad 0001
![[0000-0002-3672-2414]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3672-2414")
— King's College London, UK (and 3 more) - Muhammad Asad 0002 — University of Tokyo, Department of Creative Informatics, Japan (and 2 more)
- Muhammad Asad 0004 — International Islamic University, Islamabad, Pakistan
- Muhammad Asad 0005 — FAST National University of Computer and Emerging Sciences, Department of Computer Science, Karachi, Pakistan
- Muhammad Asad 0006 — National University of Computer and Emerging Sciences, Department of Computer Sciences, Islamabad, Pakistan
- Muhammad Asad 0007 — Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan
- Muhammad Asad 0008 — Air University, Pakistan
- Muhammad Asad 0009 — Information Technology University of the Punjab, Lahore, Pakistan
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2020 – today
- 2022
[j3]Muhammad Asad, Saad B. Qaisar:
Energy Efficient QoS-Based Access Point Selection in Hybrid WiFi and LiFi IoT Networks. IEEE Trans. Green Commun. Netw. 6(2): 897-906 (2022)- 2020
- [j2]Muhammad Asad, Abdul Basit, Saad B. Qaisar, Mudassar Ali:
Beyond 5G: Hybrid End-to-End Quality of Service Provisioning in Heterogeneous IoT Networks. IEEE Access 8: 192320-192338 (2020) - [j1]Muhammad Asad, Saad B. Qaisar, Abdul Basit:
Client-Centric Access Device Selection for Heterogeneous QoS Requirements in Beyond 5G IoT Networks. IEEE Access 8: 219820-219836 (2020) - [c8]Muhammad Asad, Saad B. Qaisar, Abdul Basit:
Client Based Access Layer QoS Provisioning in Beyond 5G IoT Networks. CommNet 2020: 1-8 - [c7]Babar Zeb, Aimal Khan, Younas Khan, Muhammad Faisal Masood, Iqra Tahir, Muhammad Asad:
Towards the Selection of the Best Machine Learning Techniques and Methods for Urinalysis. ICMLC 2020: 127-133
2010 – 2019
- 2019
- [c6]Muhammad Asad, Usman Qamar, Babar Zeb, Aimal Khan, Younas Khan:
Blood Glucose Level Prediction with Minimal Inputs Using Feedforward Neural Network for Diabetic Type 1 Patients. ICMLC 2019: 182-185 - [c5]Muhammad Asad, Usman Qamar, Aimal Khan, Rahmat Ullah Safdar:
A Systematic Literature Review of Continuous Blood Glucose Monitoring and Suggesting the Quantity of Insulin or Artificial Pancreas (AP) for Diabetic Type 1 Patients. ICMLC 2019: 539-545 - [c4]Younas Khan, Usman Qamar, Muhammad Asad, Babar Zeb:
Applying Feature Selection and Weight Optimization Techniques to Enhance Artificial Neural Network for Heart Disease Diagnosis. IntelliSys (1) 2019: 340-351 - [c3]Muhammad Asad, Younas Khan, Usman Qamar, Saba Bashir:
Blood Glucose Level Prediction Using Optimized Neural Network for Virtual Patients. IntelliSys (2) 2019: 671-683 - [c2]Muhammad Asad, Usman Qamar:
A Review of Continuous Blood Glucose Monitoring and Prediction of Blood Glucose Level for Diabetes Type 1 Patient in Different Prediction Horizons (PH) Using Artificial Neural Network (ANN). IntelliSys (2) 2019: 684-695 - 2016
- [c1]Tahira Iqbal, Moniba Iqbal, Muhammad Asad, Aihab Khan:
A source code quality analysis approach. SKIMA 2016: 142-145
Coauthor Index
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