Usman Ullah Sheikh
Universiti Teknologi Malaysia

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Hardware design of a scalable and fast 2-D hadamard transform for HEVC video encoder Heh Whit Ney; Ab Al-Hadi Ab Rahman; Ainy Haziyah Awab; Mohd Shahrizal Rusli; Usman Ullah Sheikh; Goh Kam Meng
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1401-1410

Abstract

This paper presents the hardware design of a 2-dimensional Hadamard transform used the in the rate distortion optimization module in state-of-the-art HEVC video encoder. The transform is mainly used to quickly determine optimum block size for encoding part of a video frame. The proposed design is both scalable and fast by 1) implementing a unified architecture for sizes 4x4 to 32x32, and 2) pipelining and feed through control that allows high performance for all block sizes. The design starts with high-level algorithmic loop unrolling optimization to determine suitable level of parallelism. Based on this, a suitable hardware architecture is devised using transpose memory buffer as pipeline memory for maximum performance. The design is synthesized and implemented on Xilinx Kintex Ultrascale FPGA. Results indicate variable performance obtained for different block sizes and higher operating frequency compared to a similar work in literature. The proposed design can be used as a hardware accelerator to speed up the rate distortion optimization operation in HEVC video encoders.
Distant temperature and humidity monitoring: prediction and measurement Farrukh Hafeez; Usman Ullah Sheikh; Attaullah Khidrani; Muhammad Akram Bhayo; Saleh Masoud Abdallah Altbawi; Touqeer Ahmed Jumani
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1405-1413

Abstract

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Adaptive random testing with total cartesian distance for black box circuit under test Arbab Alamgir; Abu Khari A’ain; Norlina Paraman; Usman Ullah Sheikh
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 2: November 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i2.pp720-726

Abstract

Testing and verification of digital circuits is of vital importance in electronics industry. Moreover, key designs require preservation of their intellectual property that might restrict access to the internal structure of circuit under test. Random testing is a classical solution to black box testing as it generates test patterns without using the structural implementation of the circuit under test. However, random testing ignores the importance of previously applied test patterns while generating subsequent test patterns. An improvement to random testing is Antirandom that diversifies every subsequent test pattern in the test sequence. Whereas, computational intensive process of distance calculation restricts its scalability for large input circuit under test. Fixed sized candidate set adaptive random testing uses predetermined number of patterns for distance calculations to avoid computational complexity. A combination of max-min distance with previously executed patterns is carried out for each test pattern candidate. However, the reduction in computational complexity reduces the effectiveness of test set in terms of fault coverage. This paper uses a total cartesian distance based approach on fixed sized candidate set to enhance diversity in test sequence. The proposed approach has a two way effect on the test pattern generation as it lowers the computational intensity along with enhancement in the fault coverage. Fault simulation results on ISCAS’85 and ISCAS’89 benchmark circuits show that fault coverage of the proposed method increases up to 20.22% compared to previous method.
Significance of electrodermal activity response in children with autism spectrum disorder Awais Gul Airij; Rubita Sudirman; Usman Ullah Sheikh; Lee Yoot Khuan; Nor Aini Zakaria
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1113-1120

Abstract

The human Autonomic Nervous System (ANS) controls the body’s physiological responses such as heart rate, electrodermal activity, temperature, and pupil diameter. The physiological responses are increased in the presence of a stressing stimuli and this is a typical ANS response. However, in case of children with Autism Spectrum Disorder (ASD), they suffer from autonomic dysregulation as reported in past owing to their atypical ANS response. This study investigated the ANS response of children with ASD and compares it with the response of normal children. EDA response datasets of 35 children with ASD and 55 normal children were acquired with the help of E4 wristband at a sampling rate of 4Hz. The signals were preprocessed to remove artefacts and noise and later compared. Furthermore, an SVM classifier was also used to classify the EDA response signals of normal children and children with ASD. The obtained results highlight that the ANS response of children with ASD is atypical as their EDA response is blunt and shows no significant tonic and phasic changes in EDA levels in the presence of stressing stimuli. In addition to that, an accuracy of 75% was obtained using the LF kernel of SVM classifier. The study further unfolds the hypoactive sympathetic response of children with ASD during a stressing event. Furthermore, this will help in future to anticipate the emotional responses of children with ASD such as anger, happiness, and anxiety.