Mohd Wafi Nasrudin
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Preferred name
Mohd Wafi Nasrudin
Official Name
Mohd Wafi , Nasrudin
Alternative Name
Nasrudin, Mohd Wafi
Wafi, N. M.
Main Affiliation
Scopus Author ID
57193691419
Researcher ID
FMA-4535-2022

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Adopting Ant Colony Optimization Algorithm for Pairwise T-Way Test Suite Generation Strategy

2021-07-26 , Nuraminah Ramli , Rozmie Razif Othman , Hendradi R. , Fauzi S.S.M. , Ismail I. , Mohd Zamri Zahir Ahmad , Mohd Wafi Nasrudin

Combinatorial testing or t-way testing (t represents strength) is useful to detect faults due to interactions. Pairwise testing is one type of t-way testing. The technique is effective in reducing the number of test cases without decreasing the level of coverage. Besides, its purpose is to overcome the problem of exhaustive testing that produces a great number of test cases and is impossible to be implemented due to time and cost constraints. Pairwise T-way Test Suite Generation Strategy based on Ant Colony Optimization (pTTSGA) is introduced to generate a near-optimum test suite size. Experiments have been conducted to evaluate the ability of this strategy for pairwise testing. The results are compared to benchmark results. Overall, pTTSGA produces a comparable test suite size.

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Moment Invariants Technique for Image Analysis and Its Applications: A Review

2021-07-26 , Mohd Wafi Nasrudin , Yaakob N.S. , Nor Azura Abdul Rahim , Mohd Zamri Zahir Ahmad , Ramli N. , Aziz Rashid M.S.

The Moment invariant is a feature extraction technique used to extract the global features for shape recognition and identification analysis. There are many types of Moment Invariants technique since it was introduced. To date, many applications still use the Moment Invariant technique as feature extraction technique to extract the features of any images. The reason why the Moment Invariants still valid till today because its capabilities to analyze the image due to its invariant features of an image based on rotation, translation and scaling factors. Therefore, this review paper focuses to elaborate the history of Moment invariants and its applications in related fields. The summary about the advantages and disadvantages of Moment Invariants techniques will be described at the end of this review paper.

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An IoT-based automated gate system using camera for home security and parcel delivery

2024-02-08 , Mohd Wafi Nasrudin , Jamaluddin A.F. , Ismail I. , Norfatihah Bahari , Vijayasarveswari Veeraperumal , Wan Azani Wan Mustafa , Abdul Syafiq Abdull Sukor , Abdul Rahim A.N.

The Internet of Things (IoT) has made it possible to set up smart home security and parcel delivery. Therefore, this work proposed an automated gate system using camera for home security and parcel delivery with integrated Internet of Things (IoT). An automated gate system will capture and identify the image of face visitors and delivery riders for admin authentication to open the gate and parcel box. This proposed work is controlled and monitored through mobile apps. The primary purpose and inspiration of this work are to help the delivery rider put the parcel into the parcel box provided if there is no person in the house, and the owner can pick up the parcel without being broken or robbed when she/he comes back home. When the delivery rider presses the button near the gate, the admin will receive the notification "Someone coming,". The admin will click the "okay"button and the system will take a picture using the camera in Blynk App. After the admin verifies that is the delivery rider, the admin will open the box and the delivery rider can access the parcel door box and put the goods inside the box. Another advantage of this work, it also allows familiar people to access our home. The same process with the delivery rider where the visitor needs to press the bell and the admin needs to verify before the visitor can access the single gate. The result indicates that this work is able to monitor and control the gate and parcel door box using an IoT application.

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Laguerre Krawtchouk moment invariants feature extraction technique for shape analysis

2019 , Mohd Wafi Nasrudin

The present study is concerned with the development of Feature Extraction (FE) based on the Moment Invariant techniques. The invariant properties errors were identified, when the shape is examined under the Rotation, Translation and Scaling (RTS) factors. Basically, the feature vector extracted from the original image and its counterpart variation should have similarities in their values. The feature vectors produced by the Moment Invariant techniques, that represent the images, are used as the input of classification. The performance of the percentage correct for image classification depends on the feature vectors from the image itself. Therefore, this study is motivated to develop a new algorithm based on the Moment Invariant by using the polynomials coefficients in order to reduce the invariant properties errors. The proposed technique is called as the Laguerre Moment Invariant (LGMI). The LGMI has been hybridized with the existing Moment Invariant techniques, the Zhi-Krawtchouk Moment Invariant (ZhiKMI) and Krawtchouk Moment Invariant (KMI). The new hybrid techniques are then, called as the Zhi-Laguerre Moment Invariant (ZhiLGMI) and the Laguerre-Krawtchouk Moment Invariant (LGKMI) techniques, respectively. There are five (5) existing Moment Invariant techniques that have been utilized in this work, namely the ZhiKMI, KMI, Racah-Krawtchouk Moment Invariant (RKMI), Legendre Moment Invariant (LMI) and Tchebichef Moment Invariant (TMI) techniques, which will be used to compare with the new proposed techniques. There are two main stages to examine the performance of the Moment Invariant techniques, namely the intraclass and interclass analysis. For the intraclass analysis, a set of equations has been implemented to identify the best technique between the Moment Invariants techniques based on the smallest value of Total Percentage Mean Absolute Error (TPMAE). Meanwhile, for the interclass analysis, three (3) types of Artificial Neural Network (ANN), namely Multilayer Perceptron (MLP), Simplified Fuzzy ARTMAP (SFAM) and Quality Threshold ARTMAP (QTAM), have been utilized to classify the shape images based on classes. From the intraclass results, it was found that the spatial quantization error is the main cause of the reduced Moment Invariants capability. However, the proposed LGKMI technique was found to be capable of producing the best feature vectors with the smallest value of TPMAE. The LGKMI technique is also able to classify different images with the highest percentage of correct classification with over 90% of accuracy for all the three (3) Neural Networks employed in the interclass analysis. Based on the results obtained from the intraclass and interclass analysis, it can be concluded that the proposed techniques, particularly the LGKMI technique, is found to be the best Moment Invariants technique in representing the shape feature.

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IoT based earthquake detection system

2025-09 , Norfatihah Bahari , Nor Irfan Multazam Nor Azmi , Herwansyah Lago , Mohd Wafi Nasrudin , Rashidah Che Yob , Nur Hidayah Ramli

This paper proposes an IoT based Earthquake Detection System for the early warning and quick detection of the earthquake. Earthquakes are one of the rare natural disasters in Malaysia but when the earthquake happened, it could damage infrastructure and cause deaths. This system is aimed to monitor the earthquake levels and warn people about earthquake dangers. To detect the vibration on the ground surface, an accelerometer has been connected to the microcontroller Arduino Uno R3. Then NRF24L01 transceiver module has been used to connect between the transmitter and receiver part. In order to receive the notifications about the earthquake, the ESP8266 Wi-Fi module is linked to the Blynk App. This proposed system is very user-friendly and economical, making it favourable to be used in the earthquake zones.

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Antenna Performance Enhancement using AMC Structure for 5G Frequency Range

2023-02-01 , Norfatihah Bahari , Rokhizan M.Z.N. , Rashidah Che Yob , Mohd Wafi Nasrudin , Nur Hidayah Ramli , Mohd Aminudin Jamlos , Lago H.

This paper presents a microstrip patch antenna operated at the fifth generation (5G) frequency range, which is at 3.5 GHz. To enhance the performance of the proposed antenna, an Artificial Magnetic Conductor (AMC) structure is implemented into the design. The 1x3 AMC is sandwiched between two FR-4 substrates and the performance of the proposed antenna is compared with the antenna without AMC structure. The simulated results prove that the proposed antenna offers better reflection coefficient with-50.45 dB compared to only-15.55 dB for the conventional antenna. Wider bandwidth is also achieved with 427 MHz of frequency bandwidth as opposed to only 135 MHz for the antenna without AMC. Besides that, the integration of AMC enhances the gain of the antenna when 3.7 dBi is achieved in contrast to only 3.21 dBi for the conventional antenna. Moreover, the efficiency of the antenna with AMC is also improved up to 68.54%. Furthermore, the ability to shrink 52.23% of the size of the antenna without AMC making it very favorable to be applied in 5G bands.

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Malaria Parasite Diagnosis Using Computational Techniques: A Comprehensive Review

2021-12-01 , Wan Azani Wan Mustafa , Hiam Alquran , Muhammad Zaid Aihsan , Mohd Saifizi Saidon , Wan Khairunizam Wan Ahmad , Aimi Salihah Abdul Nasir , Mohamed Mydin Hj M.Abdul Kader , Midhat Nabil Ahmad Salimi , Mohd Wafi Nasrudin

Malaria is a very serious disease that caused by the transmitted of parasites through the bites of infected Anopheles mosquito. Malaria death cases can be reduced and prevented through early diagnosis and prompt treatment. A fast and easy-to-use method, with high performance is required to differentiate malaria from non-malarial fevers. Manual examination of blood smears is currently the gold standard, but it is time-consuming, labour-intensive, requires skilled microscopists and the sensitivity of the method depends heavily on the skills of the microscopist. Currently, microscopy-based diagnosis remains the most widely used approach for malaria diagnosis. The development of automated malaria detection techniques is still a field of interest. Automated detection is faster and high accuracy compared to the traditional technique using microscopy. This paper presents an exhaustive review of these studies and suggests a direction for future developments of the malaria detection techniques. This paper analysis of three popular computational approaches which is k-mean clustering, neural network, and morphological approach was presented. Based on overall performance, many research proposed based on the morphological approach in order to detect malaria.

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Smart Classroom for Electricity-Saving with Integrated IoT System

2021-12-01 , Mohd Wafi Nasrudin , Nordin N.A. , Ismail I. , Jais M.I. , Amir Nazren Abdul Rahim , Wan Azani Wan Mustafa

Electricity-saving can be achieved through the efficient use of energy, such as turning off lights and electrical appliances when not in use. Therefore, this work proposed the smart classroom for electricity-saving with an integrated IoT System to prevent wasting electricity in the classroom. Smart Classroom means that it will detect and count the number of students entering and exiting the classroom by using a sensor system automatically. The main objective of this work is to control the lighting systems and fans by using the IoT application and sensor system. This means that when the sensor is triggered, the sensor will send data to the Blynk application software using IoT to display the status of the classroom. This proposed work is also able to detect whether a classroom is available to use or not based on the presence of people. If the classroom is being used, the Blynk application software will show the lamp and fan are ON. Otherwise, the lamps and fans are OFF if there are no people in the classroom. The result successfully shows that if the first student entering the classroom, all the lamps and fans are ON. While, if the last student exiting the classroom, all the lamps and fans are OFF. This result also indicates that electricity can be saved if all appliances in the classroom are switch OFF at the right time.

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Development of statistically modelled feature selection method for microwave breast cancer detection

2025 , Vijayasarveswari Veeraperumal , Norfadila Mahrom , Rafikha Aliana A Raof , Phak Len Al Eh Kan , Muhammad Amiruddin Ab Razak , Bavanraj Punniya Silan , Yusnita Rahayu , Mohd Wafi Nasrudin , Ahmad Ashraf Abdul Halim , Nuraminah Ramli

Microwave technology is very promising tool for breast cancer detection. Microwave transmits and receives UWB signals. UWB signals carries information of the breast cancer. UWB signals need to be pre-processed in order to remove irrelevant and redundant features. Feature extraction and feature selection methods are mostly used to remove the unwanted features. In this paper, a statistically modelled feature selection (SMFS) method is proposed for microwave breast cancer detection. Initially, performance of different feature extraction and feature selection method are analysed using Anova test (p-value) and machine learning (SVM, DT, PNN, NB) accuracy. The best feature extraction and feature selection methods are combined and tested. Based on the performance of feature extraction and feature selection method, Combined Neighbour Component Analysis (feature selection) and Statistical features (feature extraction) are combined and tested. This method is able to achieve up to 85%. The result proves two stage methods are able to improve the accuracy compared to single stage method. Therefore, SMFS is able to detect breast cancer efficiently.

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Cervical cancer situation in Malaysia: A systematic literature review

2022-01-01 , Wan Azani Wan Mustafa , Halim A. , Mohd Wafi Nasrudin , Rahman K.S.A.

Cervix cancer is one of Malaysia's most significant cancers for women (around 12.9%, with an age-standardised incidence rate of 19.7 per 100, 000). It was higher than other Asian, West, and even worldwide nations. The National Strategic Plan for Cancer Control Program 2016-2020 (Health Ministry) was presented to minimize cancer and mortality. The high incidence of cervical cancer in Malaysia is mainly due to women's insufficient knowledge about its prevention and importance. Compared with traditional literature reviews, the systemic analysis provides many advantages. A clearer review process, a more prominent field of study, and essential priorities that can manage research bias can all help to enhance these reviews. However, better integration, cooperation, and coordination between government and private sector as well as NGOs and professional organisations are essential for optimal cancer control and treatment across the country.

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