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Low-cost and portable automatic sheet cutter Mohd Syafiq Mispan; Ahmad Hafizzudin Mustafa; Hafez Sarkawi; Aiman Zakwan Jidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1837.368 KB) | DOI: 10.11591/ijece.v10i5.pp5139-5146

Abstract

Process automation is crucial to increase productivity, more efficient use of materials, better product quality, improved safety, etc. In small-medium enterprise (SME) businesses related to household retailing, one of the process automation needed is the measurement and cutting of the mat or sheet, made of rubber or polyvinyl chloride (PVC) materials. Most of the household retailers that selling the sheet, the process of measuring and cutting according to the customer’s requirements are manually performed using a measuring tape and scissors. These manual processes can cause inaccuracy in length, inefficient use of material, low productivity and reduce product quality. This paper presents a low cost and portable automatic sheet cutter using the Arduino development board, which is used to control the process of measuring and cutting the materials. The system uses a push-button where the user can set the required length and quantity of the sheet. Once the required information is set, the stepper motor rolls the sheet until the required length is satisfied. Subsequently, another stepper motor moves the cutter horizontally and cut the sheet. With the automatic sheet cutter, the material is cut with acceptable precision. The design of the automatic sheet cutter is low cost and portable which significantly suitable to be used by SME household retailers.
Android based application for visually impaired using deep learning approach Haslinah Mohd Nasir; Noor Mohd Ariff Brahin; Mai Mariam Mohamed Aminuddin; Mohd Syafiq Mispan; Mohd Faizal Zulkifli
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp879-888

Abstract

People with visually impaired had difficulties in doing activities related to environment, social and technology. Furthermore, they are having issues with independent and safe in their daily routine. This research propose deep learning based visual object recognition model to help the visually impaired people in their daily basis using the android application platform. This research is mainly focused on the recognition of the money, cloth and other basic things to make their life easier. The convolution neural network (CNN) based visual recognition model by TensorFlow object application programming interface (API) that used single shot detector (SSD) with a pre-trained model from Mobile V2 is developed at Google dataset. Visually impaired persons capture the image and will be compared with the preloaded image dataset for dataset recognition. The verbal message with the name of the image will let the blind used know the captured image. The object recognition achieved high accuracy and can be used without using internet connection. The visually impaired specifically are largely benefited by this research.
Secure lightweight obfuscated delay-based physical unclonable function design on FPGA Mohammad Haziq Ishak; Mohd Syafiq Mispan; Wong Yan Chiew; Muhammad Raihaan Kamaruddin; Mikhail Aleksandrovich Korobkov
Bulletin of Electrical Engineering and Informatics Vol 11, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i2.3265

Abstract

The internet of things (IoT) describes the network of physical objects equipped with sensors and other technologies to exchange data with other devices over the Internet. Due to its inherent flexibility, field-programmable gate array (FPGA) has become a viable platform for IoT development. However, various security threats such as FPGA bitstream cloning and intellectual property (IP) piracy have become a major concern for this device. Physical unclonable function (PUF) is a promising hardware fingerprinting technology to solve the above problems. Several PUFs have been proposed, including the implementation of reconfigurable-XOR PUF (R-XOR PUF) and multi-PUF (MPUF) on the FPGA. However, these proposed PUFs have drawbacks, such as high delay imbalances caused by routing constraints. Therefore, in this study, we explore relative placement method to implement the symmetric routing in the obfuscated delay-based PUF on the FPGA board. The delay analysis result proves that our method to implement the symmetric routing was successful. Therefore, our work has achieved good PUF quality with uniqueness of 48.75%, reliability of 99.99%, and uniformity of 52.5%. Moreover, by using the obfuscation method, which is an Arbiter-PUF combined with a random challenge permutation technique, we reduced the vulnerability of Arbiter-PUF against machine learning attacks to 44.50%.
A review paper on memory fault models and test algorithms Aiman Zakwan Jidin; Razaidi Hussin; Lee Weng Fook; Mohd Syafiq Mispan
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3048

Abstract

Testing embedded memories in a chip can be very challenging due to their high-density nature and manufactured using very deep submicron (VDSM) technologies. In this review paper, functional fault models which may exist in the memory are described, in terms of their definition and detection requirement. Several memory testing algorithms that are used in memory built-in self-test (BIST) are discussed, in terms of test operation sequences, fault detection ability, and also test complexity. From the studies, it shows that tests with 22 N of complexity such as March SS and March AB are needed to detect all static unlinked or simple faults within the memory cells. The N in the algorithm complexity refers to Nx*Ny*Nz whereby Nx represents the number of rows, Ny represents the number of columns and Nz represents the number of banks. This paper also looks into optimization and further improvement that can be achieved on existing March test algorithms to increase the fault coverage or to reduce the test complexity.
Automatic generation of user-defined test algorithm description file for memory BIST implementation Aiman Zakwan Jidin; Razaidi Hussin; Lee Weng Fook; Mohd Syafiq Mispan; Loh Wan Ying
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 11, No 2: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v11.i2.pp103-114

Abstract

Memory built-in self-test (BIST) is a widely used technique to allow the self-test and self-checking of the embedded memories on chips after the fabrication process. It can be used by implementing a standard testing algorithm available in the EDA tool library or a user-defined algorithm (UDA). This paper presents the development of software that automatically generates a description file of a UDA to be deployed for memory BIST circuit implementation using Tessent memory BIST software. It comprises the test setup and also the microprogram coding for each instruction to be executed when performing tests on embedded memories. The proposed automation software was tested by using March SR as the input algorithm and the results obtained from the simulations show that the output test patterns generated by the implemented memory BIST match the expected patterns and passed all the tests, which validated the correct functionality of the UDA description file generation. The proposed automation software also fast generation the UDA description file, which was completed in less than 500 ms.
Lightweight hardware fingerprinting solution using inherent memory in off-the-shelf commodity devices Mohd Syafiq Mispan; Aiman Zakwan Jidin; Muhammad Raihaan Kamarudin; Haslinah Mohd Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp105-112

Abstract

An emerging technology known as Physical unclonable function (PUF) can provide a hardware root-of-trust in building the trusted computing system. PUF exploits the intrinsic process variations during the integrated circuit (IC) fabrication to generate a unique response. This unique response differs from one PUF to the other similar type of PUFs. Static random-access memory PUF (SRAM-PUF) is one of the memory-based PUFs in which the response is generated during the memory power-up process. Non-volatile memory (NVM) architecture like SRAM is available in off-the-shelf microcontroller devices. Exploiting the inherent SRAM as PUF could wide-spread the adoption of PUF. Therefore, in this study, we evaluate the suitability of inherent SRAM available in ATMega2560 microcontroller on Arduino platform as PUF that can provide a unique fingerprint. First, we analyze the start-up values (SUVs) of memory cells and select only the cells that show random values after the power-up process. Subsequently, we statistically analyze the characteristic of fifteen SRAM-PUFs which include uniqueness, reliability, and uniformity. Based on our findings, the SUVs of fifteen on-chip SRAMs achieve 42.64% uniqueness, 97.28% reliability, and 69.16% uniformity. Therefore, we concluded that the available SRAM in off-the-shelf commodity hardware has good quality to be used as PUF.
Proof of concept for lightweight PUF-based authentication protocol using NodeMCU ESP8266 Mohd Syafiq Mispan; Aiman Zakwan Jidin; Muhammad Raihaan Kamaruddin; Haslinah Mohd Nasir
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.pp1392-1398

Abstract

Wireless sensor node is the foundation for building the next generation of ubiquitous networks or the so-called internet of things (IoT). Each node is equipped with sensing, computing devices, and a radio transceiver. Each node is connected to other nodes via a wireless sensor network (WSN). Examples of WSN applications include health care monitoring, and industrial monitoring. These applications process sensitive data, which if disclosed, may lead to unwanted implications. Therefore, it is crucial to provide fundamental security services such as identification and authentication in WSN. Nevertheless, providing this security on WSN imposes a significant challenge as each node in WSN has a limited area and energy consumption. Therefore, in this study, we provide a proof of concept of a lightweight authentication protocol by using physical unclonable function (PUF) technology for resource-constrained wireless sensor nodes. The authentication protocol has been implemented on NodeMCU ESP8266 devices. A server-client protocol configuration has been used to verify the functionality of the authentication protocol. Our findings indicate that the protocol used approximately 7% of flash memory and 48% of static random-access memory (SRAM) in the sensor node during the authentication process. Hence, the proposed scheme is suitable to be used for resource-constrained IoT devices such as WSN.
Signal processing for abnormalities estimation analysis Nur Fatin Shazwani Nor Razman; Haslinah Mohd Nasir; Suraya Zainuddin; Noor Mohd Ariff Brahin; Idnin Pasya Ibrahim; Mohd Syafiq Mispan
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp600-610

Abstract

Pneumonia, asthma, sudden infant death syndrome (SIDS), and the most recent epidemic, COVID-19, are the most common lung diseases associated with respiratory difficulties. However, existing health monitoring systems use large and in-contact devices, which causes an uncomfortable experience. The difficulty in acquiring breathing signals for non-stationary individuals limits the use of ultra-wideband radar for breathing monitoring. This is due to ineffective signal clutter removal and body movement removal algorithms for collecting accurate breathing signals. This paper proposes a breathing signal analysis for non-contact physiological monitoring to improve quality of life. The radar-based sensors are used for collecting the breathing signal for each subject. The processed signal has been analyzed using continuous wavelet transform (CWT) and wavelet coherence with the Monte Carlo method. The finding shows that there is a significant difference between the three types of breathing patterns; normal, high, and slow. The findings may provide a comprehensive framework for processing and interpreting breathing signals, resulting in breakthroughs in respiratory healthcare, illness management, and overall well-being.