Rosdisham Endut
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Preferred name
Rosdisham Endut
Official Name
Rosdisham, Endut
Alternative Name
Endut, Rosdisham
Endut, R.
Main Affiliation
Scopus Author ID
57189347166
Researcher ID
ABC-3290-2020

Research Output

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Enhancement receiver sensitivity under heavy attenuation effect for FSO system via double transmission technique

2024-02-08 , Thai S.A.K. , Rahman A.K. , Syed Alwee Aljunid Syed Junid , Rosdisham Endut , Norshamsuri Ali @ Hasim , Mohd Rashidi Che Beson

This paper focus on improvement of receiver sensitivity for free space optical communication. FSO communication is frequently drop performance when facing bad weather. In this research proposed new development of transmitter and receiver design in order to reduce the impact of atmospheric attenuation and increase receiver sensitivity. The analysis performance will compare with conventional amplitude shift keying (ASK) approach. Simulation result will be used to measure the performance and comparison between conventional and new proposed modulation double transmission balance receiver (DTBR) will also presented. The measurement of result will involve the effect of geometrical loss, data bit rate and distance propagation. From the result, the DTBR is increase the receiver sensitivity in term of bit error rate (BER) performance.

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Medical healthcare M2M system using the VLC system

2020-01-08 , Norhidayah Abd Aziz , Anuar Mat Safar , Mohd Rashidi Che Beson , Syed Alwee Aljunid Syed Junid , Rosdisham Endut

The RF communication has suffered from the interference and excessive latency issues. It is required a separated setup for transmission and reception of RF waves. To overcome this problem, the VLC system is a chosen technique due to high bandwidth and immunity to interference from electromagnetic sources. In this project, Optisystem Software version 15 has been chosen to study the perfomances of the VLC system in directed LOS. The performance results will be displayed on BER analyser and the simulation that has been done is iterating continuously in order to get the acceptable results. The result indicates that the reading of simulation of 1 user for both bit rate 155Mbps and 622Mbps shows the best result compared to 4 users. Without using any kind of OCDMA system, the number of users will reach the limitations which is not more than 4 users. The number of users influences the performance of the system and the result shows the decrement of BER reading which is lower than 10-9.

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Nitrate (NO3-) prediction in soil analysis using near-infrared (NIR) spectroscopy

2020-01-08 , Sabri, Mohd Shafiq Amirul , Rosdisham Endut , Mohd Rashidi Che Beson , Syed Alwee Aljunid Syed Junid , Norshamsuri Ali @ Hasim , Laili M.H. , Laili A.R. , Ismail M.N.M.

Nutrient composition in soil analysis is investigated by using nitrogen (N) in form of nitrate (NO3-) as a representative factor correlated with NIR spectroscopy spectral absorbance. NIR spectroscopy method of sampling has been tested to overcome time consuming, complex chemical analysis procedure and invasive sampling method in order to identify nitrate content in soil samples. Spectral absorbance data from range 950 nm to 1650 nm correlated with nitrate reading then tested through few pre-processing techniques. Five techniques have been listed as top performer, which are Multiplicative Scatter Correction using Common Offset (MSCCO), Multiplicative Scatter Correction (MSC), Range Normalization (RN), Mean Normalization (MN) and Reduced (R) technique. Data calibration and prediction of both data is evaluated using Partial Least Square Regression (PLSR) model. In the final analysis, R technique has achieved as top performer pre-processing technique for both calibration and prediction results, with the coefficient of determination (R2) values of 0.9991 and root mean square error (RMSE) values of 0.0886 for prediction. Overall, the correlation of NIRS absorbance data and nitrate can be obtained using PLSR model with R pre-processing technique. Henceforth, we can conclude that the NIRS method of sampling can be used to identify nitrate content in soil analysis by using time saving, non-invasive and less laborious method of sampling.

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Smart embedded-analytics sensors with cloud-based measurement system for HVAC

2020-01-08 , Aseri N.S.M. , Norshamsuri Ali @ Hasim , Mohd Najib Mohd Yasin , Mohd Rashidi Che Beson , Syed Alwee Aljunid Syed Junid , Rosdisham Endut , Nor Azura Malini Ahmad Hambali , Shapiai M.I.

HVAC system is a necessary component of environment to maintain the temperature and humidity to be kept at certain levels by using air taken from outside to ensure the indoor comfort. The purpose of the study is to reduce the electricity energy usage and cost from air conditioning by using smart embedded-analytics sensors to provide the automatic thermal control in an area. In this study, we used sensors such as temperature and humidity sensors to detect and read the currently temperature and humidity of an area monitored by a microcontroller. The cloud-based system and the sensors are connected via wifi in the presence of MQTT protocol. The protocol enables publish and subscribe method which provide the communication between sensors, cloud-based system and HVAC system. This communication can serve thermal control automatically thus resulting the optimize usage of energy from air conditioning according to the external environment temperature and humidity. The control of the temperature and humidity from air conditioning can be designed through the programming embedded in the microcontroller. The monitoring result can be displayed from the control panel to ensure how the system works.

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Temperature monitoring system using fiber Bragg grating (FBG) approach

2020-01-08 , N. Paul Rosman, Md Rosman , Mohd Rashidi Che Beson , Syed Alwee Aljunid Syed Junid , Rosdisham Endut

In this paper, a temperature monitoring system is proposed by using fiber Bragg Grating (FBG) approach. This system can be done by using OptiSystem simulation and hardware implementation. FBG was employed as it allows a reflected wavelength of light that shifts in response to variations in temperature and/or strain. Generally, FBG sensors offer ease of installation, higher accuracy, longer stability, smaller size, immunity to electromagnetic interference (EMI) and the ability to measure ultra-high and speed events. The results indicated that wavelength shifting is depended on thermal expansion coefficient of materials, which are 0.55e-6 for default and 24e-6 for aluminium. Aluminum has a better sense rather than the default one in this study. For hardware implementation, it is shown that the power level is increased from one value to another progressively.

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Development of universal OCDMA DW code family equation and structure

2024 , Syed Mohammad Ammar , Norshamsuri Ali @ Hasim , Mohamad Naufal Mohamad Saad , Syed Alwee Aljunid Syed Junid , Rosdisham Endut

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Prediction rain attenuation effect on free space optical communication Kuching/Samarahan Region

2024-02-08 , Rahman A.K. , Thai S.A.K. , Rosdisham Endut , Syed Alwee Aljunid Syed Junid , Norshamsuri Ali @ Hasim , Mohd Rashidi Che Beson

Rain attenuation is significantly affecting the FSO performance of a free-space optical communication system. Kuching/Samarahan region is situated in Malaysia state which is under tropical climate zone. The rain distribution is recorded high due to having rain season year-round. It worst when turn to monsoon season where the precipitation rate is expected high and dense. It is crucial to design the effect FSO system to ensure good quality transmission beam signal. This paper is focus on Kuching/Samarahan zone as the preliminary result to investigate the rain pattern and effect over FSO propagation. The investigation it focuses on that region is due to development that area to implement fully digital economy which need supported by high speed and capacity data that can be produced by optical technology. Therefore, FSO technology can perform this task. The rain data is collected from Malaysia Meteorology Department (Met Malaysia) which for three years 2017, 1018 and 2019. The performance will measure the effect of scattering coefficient, rain attenuation and geometrical loss. It is expected heavy rain will contribute the great impact over FSO link.

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Hybrid Dy-NFIS & RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

2021-01-01 , Ghazi A. , Syed Alwee Aljunid Syed Junid , Syed Zulkarnain Syed Idrus , Fareed A. , Al-dawoodi A. , Mohd Rashidi Che Beson , Rosdisham Endut , Ali N. , Mohsin A.H. , Abdullah S.S.

For long haul coherent optical fiber communication systems, it is significant to precisely monitor the quality of transmission links and optical signals. The channel capacity beyond Shannon limit of Single-mode optical fiber (SMOF) is achieved with the help of Multi-mode optical fiber (MMOF), where the signal is multiplexed in different spatial modes. To increase single-mode transmission capacity and to avoid a foreseen “capacity crunch”, researchers have been motivated to employ MMOF as an alternative. Furthermore, different multiplexing techniques could be applied in MMOF to improve the communication system. One of these techniques is the Optical Code Division Multiple Access (Optical-CDMA), which simplifies and decentralizes network controls to improve spectral efficiency and information security increasing flexibility in bandwidth granularity. This technique also allows synchronous and simultaneous transmission medium to be shared by many users. However, during the propagation of the data over the MMOF based on Optical-CDMA, an inevitable encountered issue is pulse dispersion, nonlinearity and MAI due to mode coupling. Moreover, pulse dispersion, nonlinearity and MAI are significant aspects for the evaluation of the performance of high-speed MMOF communication systems based on Optical-CDMA. This work suggests a hybrid algorithm based on nonlinear algorithm (Dynamic evolving neural fuzzy inference (Dy-NFIS)) and linear algorithm (Recursive least squares (RLS)) equalization for ZCC code in Optical-CDMA over MMOF. Root mean squared error (RMSE), mean squared error (MSE) and Structural Similarity index (SSIM) are used to measure performance results.

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Performance analysis of double-MIMO free space optical system under atmospheric turbulence

2021-12 , A L Tom , A K Rahman , Tamrin F K , Sahari S K , Zamhari N , Syed Alwee Aljunid Syed Junid , Norshamsuri Ali @ Hasim , Rosdisham Endut

Over the last few years, free space optical communication (FSO) has emerged as a viable alternative to radio frequency communication. It provides a promising high-speed point-to-point communication solution. However, atmospheric absorption, scattering and turbulence degrade wireless optical communication significantly, lowering device efficiency. The attenuation of signals due to the above atmospheric reasons is another major factor that affects device efficiency. The atmospheric turbulence conditions are observed implemented into different models of FSO systems, such as Single Input Single Output (SISO), Multiple Input Multiple Output (MIMO), Wavelength Division Multiplexing MIMO (WDM-MIMO) and proposed model Double Multiple Input Multiple Output (DMIMO) using the Gamma-Gamma model for a variety of reasons. The OptiSystem 7.0 software was used to run simulations to study how various weather conditions (clear, haze and fog) affected the performance of the channel. Simulation results show that implementing Double Multiple Input Multiple Output (DMIMO) techniques for FSO systems provides high quality factor for various ranges while still achieving accurate transmitted data at the receiver side. In the presence of atmospheric turbulence conditions such as clear air, haze and fog, performance improvements signal power levels, quality factor and link distance range have been demonstrated.

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Prediction model for spectroscopy using python programming

2021-12 , A A M Ismail , Norshamsuri Ali @ Hasim , Mohd Shafiq Amirul , Rosdisham Endut , Syed Alwee Aljunid Syed Junid

This paper is motivated by searching for the perfect pattern for the spectroscopy spectra using artificial neural networks (ANN) using python programming coding. The pattern from the spectroscopy is based on the absorption and emission of light and other radiation by materials in relation to the wavelength dependence of these processes. Spectral equipment such as spectrometers, spectral analysers, spectrographs, or spectrophotometers is utilised to determine spectrum values. The problem in this spectroscopy is to identify the sample or analyte, which can be solved by a prediction model for spectroscopy using Python. These problems occur when finding the best algorithm of pre-processing techniques that can predict any model accurately into an understandable format for prediction models. Various types of pre-processing techniques have been used, such as Multiplicative Scatter Correction (MSC), Inverse MSC, Extended MSC (EMSC), Extended Inverse MSC, de-trending, Standard Normal Variate (SNV) and normalisation in order to get a better r2 value. In this project, we find the r2 and the root mean square error (RMSE) to evaluate the prediction values and the actual values. First, choosing pre-processing techniques and then finding the best statistical method for constructing predictive models that produce high accuracy. We used ANN in this project as a prediction model. Based on the results, we managed to achieve our objective, which is that the prediction model has more than 90% of accuracy. Furthermore, the results show that our prediction model has 1.0 accuracy at 100 Epoch with a 0.3 learning rate. Finally, we can conclude that our prediction model can be used to predict the spectroscopy-based data format.

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