NUST Institutions Library Catalogue Search for 'au:"Zia Ur Rehman."'

Implementing Multicast Routing in a Simulation Environment using Java

By Zia ur Rehman. Islamabad, NUST School of Electrical Engineering & Computer Science, 2004 . ix, 57 p. : , Supervisors : Mr. Ahsan Ahmad, Mr. Kashif Sharif. 27 cm. +.

Place Hold on Implementing Multicast Routing in a Simulation Environment using Java

Karachi in turmoil /

By Zia Ur Rehman. . 101 pages ; 23 cm. 9789699645181

Place Hold on Karachi in turmoil /

Coding of speech at 8 K Bits/s using conjugate structure algebraic code exited linear rediction and its implementation in matlab /

By Imran , Capt Muhammad TE-35. Rawalpindi MCS 2002 . 114 :p

Place Hold on Coding of speech at 8 K Bits/s using conjugate structure algebraic code exited linear rediction and its implementation in matlab /

Speech Recognition system for controlling Electric Appliances /

By Rehman, NC Zia ur (TE-43C). Rawalpindi MCS 2010 . 49:p,;

Place Hold on Speech Recognition system for controlling Electric Appliances /

Waves & Oscillatins

By Zia-ur-Rehman. Lahore S Ghulam Ali & Sons

Place Hold on Waves & Oscillatins

VOICE FOR THE POOR ATTRACTING AND DEVELOPING MANAGEMENT TALENT

By Mohammad Zia ur Rehman. Lahore University of Management Sciences 2006 . 18 P. 05-734-2006-1

Place Hold on VOICE FOR THE POOR ATTRACTING AND DEVELOPING MANAGEMENT TALENT

Windows memory forensics tools specification test assertions and test plan

By Zia ur Rehman. Islamabad NUST-SEECS 2017 . 87p. , Supervisor: Dr. Shahzad Saleem

Place Hold on Windows memory forensics tools specification test assertions and test plan

Economic Factors and Industry Returns /

By Zia Ur Rehman, Muhammad. Islamabad: NBS - NUST, 2017 . 37 p. : ill. ; 30cm..

Place Hold on Economic Factors and Industry Returns /

Study of HCV Induced iL-12 Expression by Inhibition of JNK Activated NF-KB and AP-I Pathways /

By Farooqi, Zia-ur-Rehmam. Islamabad: ASAB - NUST, 2016 . 179 p.: ill.; , Hardcover. 35cm..

Place Hold on Study of HCV Induced iL-12 Expression by Inhibition of JNK Activated NF-KB and AP-I Pathways /

Design, Development And Fabrication Of Flying Wing Shaped Micro Air Vehicle /

By Rehman, Zia Ur . Islamabad : SMME - NUST, 2016 . 134 p. ; 30cm..

Place Hold on Design, Development And Fabrication Of Flying Wing Shaped Micro Air Vehicle /

Design and Analysis Study for a Cost Effective and/or Better Quality Hearing Aid Device

By Rehman, Muhammad Zia Ur . Islamabad : SMME - NUST, 2014 . 97 p. ; 30cm..

Place Hold on Design and Analysis Study for a Cost Effective and/or Better Quality Hearing Aid Device

اتباع سنت عقائدواحکام میں

By Zia ur rehman Alazmi. Lahore: Darusalam publications. . 95p.

Place Hold on اتباع سنت عقائدواحکام میں

Computer Aided Design

By Capt Zia Ur Rehman Satti syn no - 8. Risalpur MCE 2001 . P-89

Place Hold on Computer Aided Design

Computer aided desin for gravity retaining walls

By Capt Zia Ur Rehman Satti. Risalpur MCE 2001 . ii, 87 p:

Place Hold on Computer aided desin for gravity retaining walls

Discontinuity mapping of rocks using commercial quadcopter images

By Zia ur Rehman. Risalpur, MCE, 2019 . 59p. 30cm..

Place Hold on Discontinuity mapping of rocks using commercial quadcopter images

Soil Stabilization to Improve Strength and Mitigate Collapse Suscepibility Through Waste Marble Dust

By Capt Zulqarnain . Risalpur, MCE, 2020 . 87 pages.

Place Hold on Soil Stabilization to Improve Strength and Mitigate Collapse Suscepibility Through Waste Marble Dust

PR-SOF-1433-THERMAL VISIBLE VIDEO FUSION FOR MOVING TARGET TRACKING AND CLASSIFICATION

By MUMTAZ AON SYED, AQSA MEHREEN, ZIA UR REHMAN BABAR, SANA ZANIAB. ISLAMABAD NUST COLLEGE OF EME 2015

Place Hold on PR-SOF-1433-THERMAL VISIBLE VIDEO FUSION FOR MOVING TARGET TRACKING AND CLASSIFICATION

TH-SOF-1797-Modeling the Effect of Spherical Particles of various sizes using Direct Laser Deposition

By Zia Ur Rehman Sarwar. ISLAMABAD NUST COLLEGE OF EME 2020

Place Hold on TH-SOF-1797-Modeling the Effect of Spherical Particles of various sizes using Direct Laser Deposition

Taloohay sher

By Zia Ur Rehman Farooqi, Allama. LAHORE ISLAMIC PUBLICATIONS 2002 . 530P

Place Hold on Taloohay sher

Finite Element Modeling Of Fiber Reinforced Polymer (FRP) Composites Under Bi-axial Loading /

By Zia Ur Rehman.. Islamabad: RCMS-NUST, 2021 . 67 p. : 30cm..

Place Hold on Finite Element Modeling Of Fiber Reinforced Polymer (FRP) Composites Under Bi-axial Loading /

Analyzing the Security and Data Remnants of Android Freelancing Applications /

By Rehman, Muhammad Zia Ur . . 81 p. ;

Place Hold on Analyzing the Security and Data Remnants of Android Freelancing Applications /

Deep Learning for Improved Myoelectric Control/

By Rehman Muhammad Zia ur . . 132,p; 30,cm..

Place Hold on Deep Learning for Improved Myoelectric Control/

Study of HCV induced IL-12 expression by inhibition of jnk activated NF-kB and AP-1 Pathways/

By Zia-UR-Rehman Farooqi. . 179,p; 30,p;.

Place Hold on Study of HCV induced IL-12 expression by inhibition of jnk activated NF-kB and AP-1 Pathways/

Deep Learning for Improved Myoelectric Control /

By Zia ur Rehman, Muhammad . . 153p. , Advancement in the myoelectric interfaces have increased the use of myoelectric controlled robotic arms for partial-hand amputees as compared to body-powered arms. Current clinical approaches based on conventional (on/off and direct) control are limited to few degree of freedom (DoF) movements which are being better addressed with pattern recognition (PR) based control schemes. Performance of any PR based scheme heavily relies on optimal features set. Although, such schemes have shown to be very effective in short-term laboratory recordings, but they are limited by unsatisfactory robustness to non-stationarities (e.g. changes in electrode positions and skin-electrode interface). Moreover, electromyographic (EMG) signals are stochastic in nature and recent studies have shown that their classification accuracies vary significantly over time. Hence, the key challenge is not the laboratory shortterm conditions but the daily use. Thus, this work makes use of the longitudinal approaches with deep learning in comparison to classical machine learning techniques to myoelectric control and explores the real potential of both surface and intramuscular EMG in classifying different hand movements recorded over multiple days. To the best of our knowledge, for the first time, it also explores the feasibility of using raw (bipolar) EMG as input to deep networks. Task are completed with two different studies that were performed with different datasets. In the first study, surface and intramuscular EMG data of eleven wrist movements were recorded concurrently over six channels (each) from ten able-bodied and six amputee subjects for consecutive seven days. Performance of stacked sparse autoencoders (SSAE), an emerging deep learning technique, was evaluated in comparison with state of art LDA using offline xii classification error as performance matric. Further, performance of surface and intramuscular EMG was also compared with respect to time. Results of different analyses showed that SSAE outperformed LDA. Although there was no significant difference found between surface and intramuscular EMG in within day analysis but surface EMG significantly outperformed intramuscular EMG in long-term assessment. In the second study, surface EMG data of seven able-bodied were recorded over eight channels using Myo armband (wearable EMG sensors). The protocol was set such that each subject performed seven movements with ten repetitions per session. Data was recorded for consecutive fifteen days with two sessions per day. Performance of convolutional neural network (CNN with raw EMG), SSAE (both with raw data and features) and LDA were evaluated offline using classification error as performance matric. Results of both the short and long-term analyses showed that CNN and SSAE-f outperformed the others while there was no difference found between the two. Overall, this dissertation concludes that deep learning techniques are promising approaches in improving myoelectric control schemes. SSAE generalizes well with hand-crafted features but fails to generalize with raw data. CNN based approach is more promising as it achieved optimal performance without the need to select featur 30cm..

Place Hold on Deep Learning for Improved Myoelectric Control /

Technology Governance: Concepts & Practices /

By Zia-ur-Rehman, Azhar. Bloomington: Author House, 2017 . xiii,128 p. : 27cm.. 9781524678159

Place Hold on Technology Governance: Concepts & Practices /