Abdul Hamid Adom
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Abdul Hamid Adom
Official Name
Adom, Abdul Hamid
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Scopus Author ID
6506600412

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  • Publication
    Classification of agarwood oil using an electronic nose
    ( 2010)
    Wahyu Hidayat
    ;
    Ali Yeon Md Shakaff
    ;
    Mohd Noor Ahmad
    ;
    Abdul Hamid Adom
    Presently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.
  • Publication
    Medium Optimization for Biobutanol Production From Palm Kernel Cake (PKC) Hydrolysate By Clostridium saccharoperbutylacetonicum N1-4
    ( 2024-03-01)
    Amin M.A.
    ;
    Shukor H.
    ;
    Shoparwe N.F.
    ;
    Makhtar M.M.Z.
    ;
    Abdul Hamid Adom
    ;
    Rongwong W.
    The study aims to optimize the medium composition for biobutanol production using a Palm Kernel Cake (PKC) hydrolysate by Clostridium saccharoperbutylacetonicum N1-4. Various nutrient factors affecting biobutanol production were screened using the Plackett-Burman design. These factors included: NH4 NO3, KH2 PO4, K2 HPO4, MgSO4.7H2 O, MnSO4.7H2 O, FeSO4.7H2 O, yeast extract, cysteine, PABA, biotin, and thiamin. The results were analyzed by an analysis of variance (ANOVA), which showed that cysteine (P=0.008), NH4 NO3 (P=0.011) dan yeast extract (P=0.036) had significant effects on biobutanol production. The established model from the ANOVA analysis had a significant value of Pmodel >F = 0.0299 with an F-value of 32.82 which explains that the factors can explain in detail the variation in the data about the average and the interpretation is true with an R2 value of 0.993. The estimated maximum biobutanol production was 10.56 g/L, whereas the optimized medium produced 15.49 g/L of biobutanol. Process optimizations with optimum concentration of cysteine, NH4 NO3, and yeast extract have produced 21.33 g/L biobutanol which is a 37.7% improvement from the non-optimized medium. The findings show that PKC hydrolysate with the addition of optimal concentrations of the three types of medium namely, cysteine (0.15 g/L), NH4 NO3 (0.50 g/L), and yeast extract (1.5 g/L) during ABE fermentation, yielded a maximum biobutanol concentration of 21.33 g/L. Therefore, the results of this study provide good indications for promoting PKC hydrolysate as a new source of novel substrates with great potential in producing high biobutanol through ABE fermentation by C. saccharoperbutylacetonicum N1-4.
  • Publication
    A Review on the efficiency and accuracy of localization of moisture distributions sensing in agricultural silos
    ( 2019-12-03)
    Almaleeh A.A.
    ;
    Ammar Zakaria
    ;
    Zakaria S.M.M.S.
    ;
    Latifah Munirah Kamarudin
    ;
    Mohd Hafiz Fazalul Rahiman
    ;
    Sukor A.S.A.
    ;
    Yuzairi Abdul Rahim
    ;
    Abdul Hamid Adom
    The moisture distribution in the silos depends upon various seeds parameters such as type and size of seeds, amount of storage, external weather, and storage period as well as structural and environmental factors. It is very difficult to predict moisture distribution in silos effectively while taking all the above aspects into consideration. This study aims to investigate the efficiency and accuracy of localization of moisture distributions sensing in agricultural silo. The work is mainly focussed on three major elements: Radio Frequency (RF), tomographic imaging and classification process using machine learning. In particular, RF-based signal and volume tomographic images are used to predict the moisture distribution. Furthermore, computational intelligence techniques such as artificial neural network (ANN) is applied to develop models based on previous data. The generalization of these models towards new set of data is discussed in making sure a successful application of a model. A detailed study of the relative performance of computational intelligence techniques has been carried out based on different statistical performance criteria.
  • Publication
    Intelligent robot chair with communication aid using TEP responses and higher order spectra band features
    ( 2021)
    Sathees Kumar Nataraj
    ;
    Paulraj Murugesa Pandiyan
    ;
    Sazali Bin Yaacob
    ;
    Abdul Hamid Adom
    In recent years, electroencephalography-based navigation and communication systems for differentially enabled communities have been progressively receiving more attention. To provide a navigation system with a communication aid, a customized protocol using thought evoked potentials has been proposed in this research work to aid the differentially enabled communities. This study presents the higher order spectra based features to categorize seven basic tasks that include Forward, Left, Right, Yes, NO, Help and Relax; that can be used for navigating a robot chair and also for communications using an oddball paradigm. The proposed system records the eight-channel wireless electroencephalography signal from ten subjects while the subject was perceiving seven different tasks. The recorded brain wave signals are pre-processed to remove the interference waveforms and segmented into six frequency band signals, i. e. Delta, Theta, Alpha, Beta, Gamma 1-1 and Gamma 2. The frequency band signals are segmented into frame samples of equal length and are used to extract the features using bispectrum estimation. Further, statistical features such as the average value of bispectral magnitude and entropy using the bispectrum field are extracted and formed as a feature set. The extracted feature sets are tenfold cross validated using multilayer neural network classifier. From the results, it is observed that the entropy of bispectral magnitude feature based classifier model has the maximum classification accuracy of 84.71 % and the value of the bispectral magnitude feature based classifier model has the minimum classification accuracy of 68.52 %.
  • Publication
    Connected car: Engines diagnostic via Internet of Things (IoT)
    ( 2017-10-29)
    Azrul Fahmi A.Hamid
    ;
    Md. Tasyrif bin Abdul Rahman
    ;
    Shah Fenner Khan Mohamad Khan
    ;
    Abdul Hamid Adom
    ;
    Muhajir Ab. Rahim
    ;
    Norasmadi Abdul Rahim
    ;
    Ismail M.H.N.
    ;
    Norizan A.
    This paper is about an experiment for performing engines diagnostic using wireless sensing Internet of Thing (IoT). The study is to overcome problem of current standard On Board Diagnosis (OBD-II) data acquisition method that only can be perform in offline or wired method. From this paper it show a method to determined how the data from engines can be collected, make the data can be easily understand by human and sending data over the wireless internet connection via platform of IOT. This study is separate into three stages that is CAN-bus data collection, CAN data conversion and send data to cloud storage. Every stage is experimented with a two different method and consist five data parameter that is Revolution per Minute (RPM), Manifold Air Pressure (MAP), load-fuel, barometric pressure and engine temperature. The experiment use Arduino Uno as microcontroller, CAN-bus converter and ESP8266 wifi board as transfer medium for data to internet.
  • Publication
    Assessment of functional and dysfunctional on implant stability measurement for quality of life
    ( 2017)
    Norshahrizan Nordin
    ;
    Mohd. Mustafa Al Bakri Abdullah
    ;
    Fauziah Che Mat
    ;
    Muhammad Safizal Abdullah
    ;
    Razli Che Razak
    ;
    Abdul Hamid Adom
    This study was conducted to investigate the effect of an implant wearer comprising among orthopedic patients as well as the use of implant dentistry in Northern Malaysia. A total of 100 questionnaires were distributed and 70 questionnaires can be used to record, analyze, and test hypotheses. Data for all variables were collected through a questionnaire administered alone and analyzed by using SmartPLS V3. A total of four (4) hypotheses have been formulated and the results show that the hypothesis is supported. The results show that: (1) limit the functionality and quality of life was significantly (0.904) in connection with the implant wearer, (2) physical pain was significantly (0.845) relating to the quality of life, (3) physical discomfort was significantly (0.792) in connection with quality of life, and also (4) social discomfort is significant as well (0.809). This finding suggests that there are positive effects on the implant wearer who through life routine. The results of the study may also serve as a basis for reliable decisions related to quality of life and for the implementation of awareness campaigns that increase how the need for humanity in the field of quality involvement.
  • Publication
    Assessment of functional and dysfunctional on implant stability measurement for quality of life
    ( 2017)
    Norshahrizan Nordin
    ;
    Razli Che Razak
    ;
    Mohd. Mustafa Al Bakri Abdullah
    ;
    Muhammad Safizal Abdullah
    ;
    Fauziah Che Mat
    ;
    Abdul Hamid Adom
    This study was conducted to investigate the effect of an implant wearer comprising among orthopedic patients as well as the use of implant dentistry in Northern Malaysia. A total of 100 questionnaires were distributed and 70 questionnaires can be used to record, analyze and test hypotheses. Data for all variables were collected through a questionnaire administered alone and analyzed by using SmartPLS V3. A total of four (4) hypotheses have been formulated and the results show that the hypothesis is supported. The results show that: (1) limit the functionality and quality of life was significantly (0.904) in connection with the implant wearer, (2) physical pain was significantly (0.845) relating to the quality of life, (3) physical discomfort was significantly (0.792) in connection with quality of life, and also (4) social discomfort is significant as well (0.809). This finding suggests that there are positive effects on the implant wearer who through life routine. The results of the study may also serve as a basis for reliable decisions related to quality of life and for the implementation of awareness campaign that increase how the need for humanity in the field of quality involvement.
  • Publication
    Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors
    ( 2010)
    Ammar Zakaria
    ;
    Ali Yeon Md Shakaff
    ;
    Abdul Hamid Adom
    ;
    Mohd Noor Ahmad
    ;
    Masnan, Maz Jamilah
    ;
    Abdul Hallis Abdul Aziz
    ;
    Nazifah Ahmad Fikri
    ;
    Abu Hassan Abdullah
    ;
    Latifah Munirah Kamarudin
    An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
  • Publication
    Assessment of functional and dysfunctional on implant stability measurement for quality of life
    ( 2017-02-01)
    Norshahrizan Nordin
    ;
    Mohd. Mustafa Al Bakri Abdullah
    ;
    Fauziah Che Mat
    ;
    Muhammad Abdullah.
    ;
    Razli Che Razak
    ;
    Abdul Hamid Adom
    This study was conducted to investigate the effect of an implant wearer comprising among orthopedic patients as well as the use of implant dentistry in Northern Malaysia. A total of 100 questionnaires were distributed and 70 questionnaires can be used to record, analyze and test hypotheses. Data for all variables were collected through a questionnaire administered alone and analyzed by using SmartPLS V3. A total of four (4) hypotheses have been formulated and the results show that the hypothesis is supported. The results show that: (1) limit the functionality and quality of life was significantly (0.904) in connection with the implant wearer, (2) physical pain was significantly (0.845) relating to the quality of life, (3) physical discomfort was significantly (0.792) in connection with quality of life, and also (4) social discomfort is significant as well (0.809). This finding suggests that there are positive effects on the implant wearer who through life routine. The results of the study may also serve as a basis for reliable decisions related to quality of life and for the implementation of awareness campaign that increase how the need for humanity in the field of quality involvement.
  • Publication
    An emotion assessment of stroke patients by using bispectrum features of EEG Signals
    ( 2020)
    Choong Wen Yean
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Murugappan Murugappan
    ;
    Yuvaraj Rajamanickam
    ;
    Abdul Hamid Adom
    ;
    Mohammad Iqbal Omar
    ;
    Bong Siao Zheng
    ;
    Ahmad Kadri Junoh
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    Emotion assessment in stroke patients gives meaningful information to physiotherapists to identify the appropriate method for treatment. This study was aimed to classify the emotions of stroke patients by applying bispectrum features in electroencephalogram (EEG) signals. EEG signals from three groups of subjects, namely stroke patients with left brain damage (LBD), right brain damage (RBD), and normal control (NC), were analyzed for six different emotional states. The estimated bispectrum mapped in the contour plots show the different appearance of nonlinearity in the EEG signals for different emotional states. Bispectrum features were extracted from the alpha (8–13) Hz, beta (13–30) Hz and gamma (30–49) Hz bands, respectively. The k-nearest neighbor (KNN) and probabilistic neural network (PNN) classifiers were used to classify the six emotions in LBD, RBD and NC. The bispectrum features showed statistical significance for all three groups. The beta frequency band was the best performing EEG frequency-sub band for emotion classification. The combination of alpha to gamma bands provides the highest classification accuracy in both KNN and PNN classifiers. Sadness emotion records the highest classification, which was 65.37% in LBD, 71.48% in RBD and 75.56% in NC groups.