Muhammad Naufal Mansor
Thumbnail Image
Preferred name
Muhammad Naufal Mansor
Official Name
Muhammad Naufal, Mansor
Alternative Name
Mansor, Muhammad Naufal
Mansor, N.
Naufal Mansor, Muhammad
Mansor, Muhammad Naufal Bin
Mansor, M. N.
Main Affiliation
Scopus Author ID
36469792500
Researcher ID
DHG-8694-2022

Research Output

Filters

16
4 1
16
Reset filters

Settings
Now showing 1 - 10 of 16
  • Publication
    A modified retinex illumination normalization approach for infant pain recognition system
    ( 2014)
    Muhammad Naufal Mansor
    Pains in newborn babies are monitored in a Neonatal Intensive Care Unit (NICU) for medical treatment. Pain in newborns can be detected by studying their facial appearance. Even though the outcome is acceptable, it is not adequately vigorous to be used in unpredictable, non-ideal situations such as noise and varying illumination environment. First, to improve the noise cancellation robustness an adaptive median filter (AMF) is proposed. Mean and variance of median values are selected to generate a weight for each window part of the images such as 3x3, 5x5 or 7x7. Various linear and nonlinear filters are adopted to eliminate the noise in the images. Quantitative comparisons are performed between these filters with our AMF in terms of Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Image Enhancement Factor (IEF) and Mean Structural SIMilarity (MSSIM) Index. The average results show improvement in terms of 40.63 db for PSNR, 6.01 for MSE, 258.09 for IEF and 0.97 for MSSIM respectively. In this work a novel method of illumination invariant normalization known as Modified Retinex Normalization (MRT) for preprocessing of infant face recognition is proposed. This is based on a modified retinex model that combines with histogram normalization for filtering the illumination invariant. The proposed method is compared to other methods like Single scale Retinex (SSR), Homomorphic method (HOMO), Single Scale Self Quotient Image (SSQ), Gross and Brajovic Technique (GBT), DCT-Based Normalization (DCT), Gradientfaces-based normalization technique (GRF), Tan and Triggs normalization technique (TT), and Large-and small-scale features normalization technique (LSSF) for evaluation with Infant Classification of Pain Expressions (COPE) database. Several experiments were performed on COPE databases. Single PCA, LBP and DCT feature extraction information yielded a good recognition result. However, by summing these three, it gives more robustness to noise and illumination classification rate because the sum rule was the most resilient to estimate errors and gives higher than 90% accuracies of pain and no pain detection. The new illumination normalization and combination of features gives higher results of more than 90% on five different classifiers with various algorithms such as k-nearest neighbors (k-NN), Fuzzy k-nearest neighbors (FkNN), Linear Discriminat Analysis (LDA), Feed Forward Neural Network (FFNN), Probabilistic Neural Network (PNN), General regression Neural Network (GRNN), SVM Linear kernel (SVMLIN), SVM RBF kernel (SVMRBF), SVM MLP kernel (SVMMLP) and SVM Polynomial kernel (SVMPOL) with different performance measurement such as Sensitivity, Specificity, Accuracy, Area under Curve (AUC), Cohen's kappa (k), Precession , F-Measure and Time Consumption .
  • Publication
    Entropy virus microscopy images recognition via neural network classifiers
    ( 2017-07-02)
    Afiq Ahmad Shakri
    ;
    Syahrul Affandi Saidi
    ;
    Haryati Jaafar
    ;
    Muhammad Naufal Mansor
    ;
    Wan Azani Wan Mustafa
    ;
    Ahmad Kadri Junoh
    One of the topics that are commonly in focus of object detection and image recognition is virus detection. It is well known that to learn and detecting virus proven to be a challenging and quite complex task for computer systems under different noise level. This research work investigates the performances of preprocessing stages with Entropy feature extraction with Feed Forward Neural Network (FFNN) classifier under various levels of noise. The real time experiment conducted proved that the method proposed are efficient, robust, and excellent of which it has produced a results accuracy of up to 88% for biological viruses images classification.
  • Publication
    Breast Cancer Detection on X-Tray Mammogram Images
    ( 2023-01-01)
    Azmi M.A.A.
    ;
    Wan Azani Wan Mustafa
    ;
    Alquran H.
    ;
    Aziz A.A.
    ;
    Muhammad Naufal Mansor
    ;
    Alzubaidi L.H.
    ;
    Hussein A.H.A.
    Breast cancer (BC) is a common cancer affecting women everywhere in world. Mammography is identified and efficient technique to detect primary BC. The aim of project is for detect BC on mammogram in order to categorize disease by image processing when comparing with a previous technique. Through utilizing conventional methods, it creates it complex for radiology to detect cancer from patient's breast. In addition, there are environmental disturbances and technical problems if using the old method. Image processing techniques was separated to numerous elements. The elements are input, pre-processing, segmentation, morphological, object classification and classification. First pre-processing was done through Weiner and Median filter. Then, thresholding method on segmentation and finally, morphological will eliminate limitations at a segmentation. The image classified into 2 classes like normal and tumor. Both type of images analyzed based on elements. Additionally, it comprises a building of Graphical User Interface (GUI) which is utilized to generate the system as user-friendly. The developed model attain accuracy of 93.71 %, specificity of 82.53 % sensitivity of 94.36% for tumorous images.
  • Publication
    Contrast virus microscopy images recognition via k-NN classifiers
    ( 2017-07-02)
    Afiq Ahmad Shakri
    ;
    Syahrul Affandi Saidi
    ;
    Muhammad Naufal Mansor
    ;
    Haryati Jaafar
    ;
    Ahmad Kadri Junoh
    ;
    Wan Azani Wan Mustafa
    One of the topics that are commonly in focus of object detection and image recognition is virus detection. It is well known that to learn and detecting virus proven to be a challenging and quite complex task for computer systems under different noise level. This research work investigates the performances of preprocessing stages with Contrast feature extraction with K-Nearest Neighbor (KNN) classifier under various levels of noise. The real time experiment conducted proved that the proposed method are efficient, robust, and excellent of which it has produced a results accuracy of up to 88% for biological viruses images classification.
  • Publication
    Arduino IOT Based Inventory Management System Using Load Cell and NodeMCU
    ( 2023-11-01)
    Muhammad Naufal Mansor
    ;
    Noor Anida Abu Talib
    ;
    Syahrul Affandi Saidi
    ;
    Wan Azani Wan Mustafa
    ;
    Zamri N.F.
    Nowadays, everything is made simpler with information and communication technological advancements. It is preferable to track and monitor using devices rather than perform it manually. This resulted in the rapid growth of Internet of Things (IoT) technology and relevant markets. Low cost IoT products has made access to IoT much easier and desirable. These low cost IoT devices and related technologies are widely used in areas such as educational, transportation, tracking, inventory management and many more. The use of Arduino and RFID in the inventory management system lacks in some areas including hardware limitations. In conjunction to the limitation of using an Arduino and RFID technology, this project aims to develop an IoT based inventory management system that incorporates the uses of a NodeMCU and a load cell. In comparison of the NodeMCU to an Arduino, the NodeMCU stands out with the built in Wi-Fi module with much higher processor and additional properties of it being much smaller. While the use of a load cell is much more convenient as to suit all kinds of inventory management needs compared to the use of RFID that suits better to larger scale businesses with larger inventory and massive stocks. Towards the end, this project is expected to ease inventory management by the implementation of IoT with IoT Based Inventory Management System using Load Cell and NodeMCU. The project will generate the inventory count and automatically stores data in the cloud platform. These data can be accessed with internet connection. The project also alerts users when the inventory is low or high in balance. The output of the project is that the project’s working prototype was successfully developed. Overall, the project is a success as all the objectives of the project was successfully achieved.
  • Publication
    Extended median filter for salt and pepper noise
    ( 2017-01-01)
    Bilal Charmouti
    ;
    Ahmad Kadri Junoh
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Muhammad Naufal Mansor
    ;
    Mohd Zamri Hasan
    ;
    Mohd Yusoff Mashor
    Image have a significant importance in many fields in human life such as, in medicine, photography, biology, astronomy, industry and defence. Thus, it attracts the attention of large number of researchers, among them those interested in preserving the image features from any factors that may reduce the image quality. One of these factors is the noise which affects the visual aspect of the image and makes others image processing more difficult. Thus far, solving this noise problem remains a challenge point for the researchers in this field, a huge number of image denoising techniques have been introduced in order to remove the noise with taking care of the image featurs, in other words, get the best similarity to the original image from the noisy one. However, beside the enormous amount of researches and studies which adopt several mathematical concepts (statistics, probabilities, modeling, PDEs, wavelet, fuzzy logic, etc.), the findings proved to be inconclusive yet. From this point, the current study aims to introduce a new denoising method for removing salt & pepper noise from the digital image through developed Median filter, so as to overcome this problem of noise and achieve a good image restoration.
  • Publication
    Development of Surveillance Hovercraft via Arduino
    ( 2024-02-01)
    Muhammad Naufal Mansor
    ;
    Syahrul Affandi Saidi
    ;
    Wan Azani Wan Mustafa
    ;
    Roejhan Md Kawi
    ;
    Mohd Aminudin Jamlos
    ;
    Talib N.A.A.
    ;
    Mohd Zamri Hasan
    The current research focuses on the development of hovercraft via Arduino. The vehicle is designed with bag skirt structure in order to reduce friction for smooth operation. Nowadays, there are a lot of natural disaster occur in everywhere especially flood. However, hovercraft is a vehicle that need a driver to drive which can cause a danger to the rescuer. Based on this problem, a wireless hovercraft is needed to develop. This study explains a hovercraft which is able to control the movement of the hovercraft from the surface. The design of the hovercraft was successfully made by using AutoCAD software. Furthermore, the material of the body was made from the insulation foam while the microprocessor is Arduino UNO R3. There are two brushless DC motors and one servo motor that used for this hovercraft. The first brushless DC motor which is located below the hovercraft is used as a hover operation, while the second motor located behind it is used to ensure the hovercraft move forward. In addition, the performance of the hovercraft was successfully tested on the 3 different surfaces. As a result, the highest performance is on the cement while the lowest is on the grass.
  • Publication
    Liquid Composition Identification and Characteristic Measurement Using Ultrasonic Transmission Technique via Neural Network
    ( 2023-08-01)
    Muhammad Naufal Mansor
    ;
    Yahya S.
    ;
    Wan Azani Wan Mustafa
    ;
    Habibah Mokhtaruddin
    ;
    Syahrul Affandi Saidi
    ;
    Ilham Shafini Ahmad Mahyudin
    ;
    Mohd Aminudin Jamlos
    ;
    Noor Anida Abu Talib
    ;
    Mohd Zamri Hasan
    This project is to determine the composition of liquids solvent by using the ultrasonic frequency signal from echoscope scan machine. The transmission technique of ultrasonic signal is focused. On the research experiment, studies on mixing of distilled water with control sodium chloride (Kitchen Salt), kitchen sugar and monosodium glutamate (MSG). The Parameters such as Fast Fourier Transform (FFT) which is the parameters are using to identify the ratio of composition of liquid solvent. The feature extraction of median, average and root mean square (RMS) from FFT is represented with different result analysis such as sensitivity, specificity, accuracy, Area under curve, kappa, F-measure and precision. The results performed more than 90% with Neural Network.
      1
  • Publication
    Development of a Multi-Fan System (MFS) in a Plant Factory with Artificial Light
    ( 2022-01-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Zol Bahri Razali
    ;
    Wan Azani Wan Mustafa
    ;
    Muhammad Naufal Mansor
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Akbar M.F.
    ;
    Osman M.K.
    ;
    Setumin S.
    ;
    Idris M.
    ;
    Bin Ramli M.A.
    ;
    Sharifful Mizam N.S.
    A plant factory is a factory that grows plants indoors. These indoor farms could be the key to solve food shortages in the world. Plant factories are operated in indoor spaces under controlled cultivation conditions such as light, temperature and humidity. Then, a multi-fan system (MFS) for single culture beds. The MFS had four fans which were installed on both the front and back sides of culture beds to generate airflow from two opposite horizontal directions by using the Internet of Things (IoT) via the access and connection of smartphone devices. The fans that push the air into the culture bed were air inlets while those that pull the air out of the culture bed were air outlets. The main problem is in plant factories with artificial light, a heat that is usually used to control the environmental parameters and the air velocity is generally lower than the optimum range required for plant growth. Compare to a plant factory without using a multi-fan, it no circulation of air in the container to ensure continuous gas exchange. This reduction in gas exchange can impact calcium uptake by the plants. The gas exchange makes the tip burn. Tip burn can have a significant impact on the salability of a lettuce crop. Based on the limitations that have been highlighted previously, this research has been carried out by using multi-fan and without multi-fan. To get the data that need to be compared. Then, to improve the airflow in a plant factory with artificial light and prevent tip burn occur on the lettuce itself. In a nutshell, this prototype is expected to help plant factories reduce tip burn symptoms on leaf lettuce and the airflow can improve the growth of indoor cultured lettuce.
      2  1
  • Publication
    Aquaponic Ecosystem Monitoring with IOT Application
    ( 2023-08-01)
    Muhammad Naufal Mansor
    ;
    Mohd Zamri Hasan
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Wan Azani Wan Mustafa
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Aminudin Jamlos
    ;
    Noor Anida Abu Talib
    Aquaculture is an agricultural technology that combines aquaculture (fish farming activities) with hydroponic activities (planting crops without soil media) in one circulation. The most important element in aquaculture is the existence of fish, plants, and bacteria. These three elements form a mutually beneficial relationship or symbiotic mutualism. The main purpose of the aquaculture system is to maintain water quality and reduce ammonia levels from the water so that it can be utilized by other organisms. In addition, aquaculture can also save space and can produce two types of human food simultaneously, plants and livestock. Agricultural technology design with Aquaculture also uses the concept of Internet of Things (IoT) as information from sensors and sensors of value generator is accessible through applications installed on smartphones from anywhere with an Internet connection. Development of monitoring of aquaponic ecosystems with IoT systems was developed using a program using micro-controls to control temperature, humidity, pH levels and water pumps. There are some improvements made to this project.
      2  2