Asral Bahari Jambek
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Asral Bahari Jambek
Official Name
Asral , Bahari Jambek
Alternative Name
Jambek, Asral Bahari
Bahari Jambek, Asral
Jambek, Asral Bin Bahari
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Scopus Author ID
57195722408
Researcher ID
AAG-2050-2021

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  • Publication
    Design and analysis of a two-stage OTA for sensor interface circuit
    ( 2014)
    Siti Nur Syuhadah Baharudin
    ;
    Asral Bahari Jambek
    ;
    Rizalafande Che Ismail
    This paper discusses the design of an operational transconductance amplifier (OTA) circuit foruse in a capacitive sensor interface circuit. The OTA converts a differential voltage input into the current as part of a switched capacitor integrator module. In this paper, a two-stage OTA is proposed which has high gain, high output swing and low noise. The circuit wasimplemented using 0.13μm Silterra CMOS technology and simulated using the Mentor Graphic Design Architect software package. The results show that the OTA is able to achieve74dB gain and 20KHz bandwidth when operated using a 2.5V power supply, with a total power consumption of 1.3mW. © 2014 IEEE.
  • Publication
    Investigation of Scribing Quality Defect of Thin Film Solar Cell Using Machine Vision
    ( 2020-12-18)
    Shuaimi R.
    ;
    Rizalafande Che Ismail
    ;
    Hazwan Hadzir M.N.
    ;
    Mohd Annuar Mohd Isa
    ;
    Asral Bahari Jambek
    Laser micromachining provide significant effect in thin film solar industrial field especially in determining cell efficiency of each panels. However, there is an issue in determining scribing failure or defect on solar module. This research aims to investigate the defects of laser micromachining process in thin film solar module in manufacturing fields. Machine vision inspection system is used as inspection tools and to investigate the defect of laser micromachining in thin film solar cells. As a result, two major defects is define which is scribe line quality and scribe line position defects in every scribe line. By identifying the defect cause by laser micromachining through machine vision, quality control plan can be taken together to prevent reoccurrence.
  • Publication
    Performance evaluation of arithmetic coding data compression for internet of things applications
    ( 2019)
    Nor Asilah Khairi
    ;
    Asral Bahari Jambek
    ;
    Rizalafande Che Ismail
    Wireless Sensor Network (WSN) is known for its autonomous sensors, where it has been found to be useful during the development of Internet of Things (IoT) devices. However, WSN is also known for its limited energy supply and memory space, as it carries small-sized batteries and memory space. Hence, a data compression approach has been introduced in this paper with the purpose of solving this particular issue. This paper focused on the performance of the Arithmetic Coding algorithm. Temperature (Temp), Sea-Level Pressure (Pressure), stride interval (Stride), and heart rate (BPM) were chosen as the dataset in this project. Based on the results, the compression ratio of Temp, Pressure, Stride, and BPM were 0.428, 0.255, 0.217, and 0.159 respectively. From this analysis, BPM produced the best compression ratio. Undeniably, the Arithmetic Coding algorithm is one of the best methods to compress real-world datasets. Hence, by using this approach, it can reduce the usage of energy and memory space.</span><table class="MsoTableGrid" style="width: 444.85pt; border-collapse: collapse; border: none; mso-border-alt: solid windowtext .5pt; mso-yfti-tbllook: 1184; mso-padding-alt: 0in 5.4pt 0in 5.4pt;" width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr style="mso-yfti-irow: 0; mso-yfti-firstrow: yes; mso-yfti-lastrow: yes; height: 63.4pt;"><td style="width: 290.6pt; border: none; border-top: solid windowtext 1.0pt; mso-border-top-alt: solid windowtext .5pt; padding: 0in 5.4pt 0in 5.4pt; height: 63.4pt;" valign="top" width="387"><p class="MsoNormal" style="margin-top: 6.0pt; text-align: justify;"><span style="font-size: 9.0pt; color: black; mso-bidi-font-style: italic;">Wireless Sensor Network (WSN) is known for its autonomous sensors, where it has been found to be useful during the development of Internet of Things (IoT) devices. However, WSN is also known for its limited energy supply and memory space, as it carries small-sized batteries and memory space. Hence, a data compression approach has been introduced in this paper with the purpose of solving this particular issue. This paper focused on the performance of the Arithmetic Coding algorithm. Temperature (Temp), Sea-Level Pressure (Pressure), stride interval (Stride), and heart rate (BPM) were chosen as the dataset in this project. Based on the results, the compression ratio of Temp, Pressure, Stride, and BPM were 0.428, 0.255, 0.217, and 0.159 respectively. From this analysis, BPM produced the best compression ratio. Undeniably, the Arithmetic Coding algorithm is one of the best methods to compress real-world datasets. Hence, by using this approach, it can reduce the usage of energy and memory space.
      1  9
  • Publication
    Image data compression using fast Fourier transform (FFT) technique for wireless sensor network
    ( 2024-02-08)
    Haron M.H.
    ;
    Mohd Nazrin Md Isa
    ;
    Muhammad Imran Ahmad
    ;
    Arshad M.A.M.
    ;
    Asral Bahari Jambek
    ;
    Siti Zarina Md Naziri
    ;
    Hussin R.
    ;
    Harun A.
    ;
    Rizalafande Che Ismail
    ;
    Shaiful Nizam Mohyar
    Agricultural settings present unique challenges for the transmission of huge amounts of images over long-range wireless networks. It is challenging to remotely gather data for transmission over a wireless network in research areas due to a lack of basic amenities like internet connections, especially in distant agricultural areas. In this research, the Fast Fourier Transform (FFT) method was used in conjunction with the Discrete Cosine Transform (DCT) method of image compression to achieve a higher compression ratio. In order for a Wireless Sensor Network (WSN) to provide compressed image data to a wireless based station, a LoRaWAN network has been identified. Low-power LoRaWAN networks may regularly transmit compressed images from an agricultural region to a monitoring system up to 15 km away. Images of golden apple snails were collected for this study from a variety of sources. The procedure was coded in MATLAB so that it could be run with input images being judged by the created algorithm. The input images can be compressed with a range of compression ratios (CR) from 3.00 to 50.00, as shown by the simulation results. Compressed image quality is measured not only by the above-mentioned criteria, but also by Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). According to the numbers, the best achievable compression ratio is 49.04, with an MSE of 172.72 and a PSNR of 25.75 at its highest.
      15  1
  • Publication
    Improved addition and subtraction in logarithmic number system: Technique and analysis
    ( 2013)
    Rizalafande Che Ismail
    ;
    N. Norzahiyah
    ;
    Asral Bahari Jambek
    Logarithmic Number System (LNS) is an alternative beside Floating Point (FLP) when an application requires a large dynamic range in the number processed. It allows simple implementation of multiplication and division using a Fixed Point (FXP) method without rounding error. In contrast, LNS addition and subtraction become more complex procedure. Therefore over the year, difference ways of improving the addition and subtraction function have been purposed. In this paper several techniques have been discussed and analysed such as direct lookup table, interpolation, table partitioning and co-transformation for approximating LNS addition and subtraction.
      1  10