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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science

Norsuzila Ya’acob

Universiti Teknologi MARA

Author-ID : 2378812

Computer Science & IT Electrical & Electronics Engineering

Published : 9 Documents Claim Missing Document

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Hardware simulation for exponential blind equal throughput algorithm using system generator Yusmardiah Yusuf; Darmawaty Mohd Ali; Norsuzila Ya’acob
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Scheduling mechanism is the process of allocating radio resources to User Equipment (UE) that transmits different flows at the same time. It is performed by the scheduling algorithm implemented in the Long Term Evolution base station, Evolved Node B. Normally, most of the proposed algorithms are not focusing on handling the real-time and non-real-time traffics simultaneously. Thus, UE with bad channel quality may starve due to no resources allocated for quite a long time. To solve the problems, Exponential Blind Equal Throughput (EXP-BET) algorithm is proposed. User with the highest priority metrics is allocated the resources firstly which is calculated using the EXP-BET metric equation. This study investigates the implementation of the EXP-BET scheduling algorithm on the FPGA platform. The metric equation of the EXP-BET is modelled and simulated using System Generator. This design has utilized only 10% of available resources on FPGA. Fixed numbers are used for all the input to the scheduler. The system verification is performed by simulating the hardware co-simulation for the metric value of the EXP-BET metric algorithm. The output from the hardware co-simulation showed that the metric values of EXP-BET produce similar results to the Simulink environment. Thus, the algorithm is ready for prototyping and Virtex-6 FPGA is chosen as the platform.

Estimation of TRMM rainfall for landslide occurrences based on rainfall threshold analysis Noraisyah Tajudin; Norsuzila Ya’acob; Darmawaty Mohd Ali; Nor Aizam Adnan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Landslide can be triggered by intense or prolonged rainfall. Precipitation data obtained from ground-based observation is very accurate and commonly used to do analysis and landslide prediction. However, this approach is costly with its own limitation due to lack of density of ground station, especially in mountain area. As an alternative, satellite derived rainfall techniques have become more favorable to overcome these limitations. Moreover, the satellite derived rainfall estimation needs to be validated on its accuracy and its capability to predict landslide which presumably triggered by rainfall. This paper presents the investigation of using the TRMM-3B42V7 data in comparison to the available rain-gauge data in Ulu Kelang, Selangor. The monthly average rainfall, cumulative rainfall and rainfall threshold analysis from 1998 to 2011 is compared using quantitative statistical criteria (Pearson correlation, bias, root mean square error, mean different and mean). The results from analysis showed that there is a significant and strong positive correlation between the TRMM 3B42V7 and rain gauge data. The threshold derivative from the satellite products is lower than the rain gauge measurement. The findings indicated that the proposed method can be applied using TRMM satellite estimates products to derive rainfall threshold for the possible landslide occurrence.

Linear regression and R-squared correlation analysis on major nuclear online plant cooling system Ahmad Azhari Mohamad Nor; Mohd Sabri Minhat; Norsuzila Ya’acob; Murizah Kassim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3998-4008

The primary cooling system is an integral part of a nuclear reactor that maintains reactor operational safety. It is essential to investigate the effects of the cooling system parameter before implementing predictive maintenance techniques in the reactor monitoring system. This paper presents a linear regression and R-squared correlation analysis of the nuclear plant cooling system parameter in the TRIGA PUSPATI Reactor in Malaysia. This research examines the primary cooling system's temperature, conductivity, and flow rate in maintaining the nuclear reactor. Data collection on the primary coolant system has been analyzed, and correlation analysis has been derived using linear regression and R-squared analysis. The result displays the correlation matrix for all sensors in the primary cooling system. The R-squared value for TT5 versus TT2 is 89%, TT5 versus TT3 is 94%, and TT5 against TT4 is 66% which shows an excellent correlation to the linear regression. However, the conductivity sensor CT1 does not correlate with other sensors in the system. The flow rate sensor FT1 positively correlates with the temperature sensor but does not correlate with the conductivity sensor. This finding can help to better develop the predictive maintenance strategy for the reactor monitoring program.

Co-Authors Adiba Abd Ghafar Ahmad Azhari Mohamad Nor Ainnur Eiza Azhar Ainnur Eiza Mohd Azhar Aziean Mohd Azize Azita Laily Yusof Azita Laily Yusof Azita Laily Yusof Azlina Idris Darmawaty Mohd Ali Divine Senanu Ametefe Mohd Nor Md Tan Mohd Sabri Minhat Murizah Kassim Nani Fadzlina Naim Nani Fadzlina Naim Nor Aizam Adnan Noraisyah Tajudin Norfishah Ab Wahab Norlela Ishak Nur Jumaatul Hidayati Binti Mohammad Roslina Mohamad Ruhani Ab Rahman Siti Norbaiyah Rohaizad Suzi Seroja Binti Sarnin Suzi Seroja Sarnin Suzi Seroja Sarnin Wan Norsyafizan Wan Mohamad Yusmardiah Yusuf

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