Papers by Maz Jamilah Masnan
AIP Conference Proceedings, 2015
AIP Conference Proceedings, 2016
Tropical Life Sciences Research, 2020
Highlights • Fifty accessions of Harumanis harvested from different location and tree age were ev... more Highlights • Fifty accessions of Harumanis harvested from different location and tree age were evaluated based on their morphological variation. • The result of Principal Component Analysis (PCA) provided a good approximation of the data which majorly contributed by parameters of weight, fruit dimensional characteristics, peel percentage and hue angle, h. • Preliminary screening of important morphological characteristics which contribute to the phenotypic diversity of Harumanis is successfully achieved.
Sensors, 2011
The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The sam... more The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue)
Journal of Telecommunication, Electronic and Computer Engineering, May 30, 2018
Journal of Physics: Conference Series, 2021
Extreme learning machine (ELM) is a special type of single hidden layer feedforward neural networ... more Extreme learning machine (ELM) is a special type of single hidden layer feedforward neural network that emphasizes training speed and optimal generalization. The ELM model proposes that the weights of hidden neurons need not be tuned, and the weights of output neurons can be calculated by finding the Moore-Penrose generalized inverse method. Thus, the ELM classifier is suitable to use in a homogeneous ensemble model due to the untuned random hidden weights which promote diversity even with the same training data. This paper studies the effectiveness of the ELM ensemble models in solving small sample-sized classification problems. The research involves two variants of the ensemble model: the normal ELM ensemble with majority voting (ELE), and the random subspace method (RS-ELM). To simulate the small sample cases, only 30% of the total data will be used as the training data. Experiment results show that the RS-ELM model can outperform a multi-layer perceptron (MLP) model under the as...
Journal of Intelligent & Fuzzy Systems, 2019
2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES), 2014
The three different culture media namely blood agar, Mueller Hinton and MacConkey were used in th... more The three different culture media namely blood agar, Mueller Hinton and MacConkey were used in this study to identify and classify the causative bacteria on diabetic foot infection using electronic nose (E-nose). All the samples were taken from the clinical specimens using standard swabbing technique. E-nose consisting an array of 32 conducting polymer sensors was used to detect volatile organic compounds (VOCs) released by the bacteria in the infected areas. The VOC profiles of three bacterial groups from three genera namely Escherichia coli (ECOLI), Staphylococcus aureus (SAU) and Pseudomonas aeruginosa (PAE) were characterized using statistical classification technique called Linear Discriminant Analysis (LDA) to differentiate between different agars used with individual bacteria species which accounted for all the data. Although these methods are still fundamental, there is an increasing shift toward molecular diagnostics of bacteria. This investigation showed that the E-nose was able to correctly classify different bacterial species in all three culture media with up to 90% accuracy.
Mahalanobis distance values are commonly in the range of 0 to where higher values represent great... more Mahalanobis distance values are commonly in the range of 0 to where higher values represent greater distance between class means or points. The increase in Mahalanobis distance is unbounded as the distance multiply. To certain extend, the unbounded distance values pose difficulties in the evaluation and decision for instance in the sensors closeness test. This paper proposes an approach to [0, 1] bounded Mahalanobis distance that enable researcher to easily perform sensors closeness test. The experimental data of four different types of rice based on three different electronic nose sensors namely InSniff, PEN3, and Cyranose320 were analyzed and sensor closeness test seems successfully performed within the [0, 1] bound.
Journal of Intelligent & Fuzzy Systems, 2015
Profoundly hearing-impaired community (PHIC) cannot moderate wisely an acoustic noise emanated fr... more Profoundly hearing-impaired community (PHIC) cannot moderate wisely an acoustic noise emanated from moving vehicle in outdoor environment. Due to this, they have difficulties to distinguish type and the distance of moving vehicles especially the one comes from the rear. Hence, they are at risk whenever they are outdoors. In this paper, a simple system is proposed to identify the type and distance (zone-based) of a moving vehicle using a multi-classifier system (MCS). One-third octave filter bands approach has been used for extracting the significant feature from the noise emanated by the moving vehicle. The extracted features were associated with the type and zone of the moving vehicle and the MCS based on multilayer perceptron has been developed. The developed multilayer perceptron model with the same hidden neuron and training algorithm has been proposed for MCS. This network has been tested for single classifier and MCS. The developed MCS has improved the classification accuracy compared to single classifier.
Sensors, 2010
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. F... more 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.
Journal of Telecommunication, Electronic and Computer Engineering, 2018
Random Linear Oracle (RLO) utilized classifier fusion-selection approach by replacing each classi... more Random Linear Oracle (RLO) utilized classifier fusion-selection approach by replacing each classifier with two mini-ensembles separated by an oracle. This research investigates the effect of t-test feature selection toward classification performance of RLO ensemble method. Naive Bayes (NB) classifier has been chosen as the base classifier due to its elegant simplicity and computationally inexpensive. Experiments were carried out using 30 data sets from UCI Machine Learning Repository. The results showed that RLO ensemble could greatly improve the ability of NB classifier in dealing with more data with different properties. Moreover, RLO ensemble receives benefits from feature selection algorithm, with a properly selected number of features from ttest, the performance of ensemble can be improved.
Journal of Telecommunication, Electronic and Computer Engineering, 2017
Random Linear Oracle (RLO) ensemble replaced each classifier with two mini-ensembles, allowing ba... more Random Linear Oracle (RLO) ensemble replaced each classifier with two mini-ensembles, allowing base classifiers to be trained using different data set, improving the variety of trained classifiers. Naive Bayes (NB) classifier was chosen as the base classifier for this research due to its simplicity and computational inexpensive. Different feature selection algorithms are applied to RLO ensemble to investigate the effect of different sized data towards its performance. Experiments were carried out using 30 data sets from UCI repository, as well as 6 learning algorithms, namely NB classifier, RLO ensemble, RLO ensemble trained with Genetic Algorithm (GA) feature selection using accuracy of NB classifier as fitness function, RLO ensemble trained with GA feature selection using accuracy of RLO ensemble as fitness function, RLO ensemble trained with t-test feature selection, and RLO ensemble trained with Kruskal-Wallis test feature selection. The results showed that RLO ensemble could si...
In this paper, an assessment for students’ ability in critical thinking within statistics content... more In this paper, an assessment for students’ ability in critical thinking within statistics content is discussed. Despite instructors’ awareness on critical thinking as one of essentials 21 century skills, it remains unclear about how to develop the instructional framework for teaching, learning and assessing critical thinking in statistics domain. Moreover, there is an urgency to reform statistics classroom include; the way instructor teach statistics, the way students learn statistics and how to assess statistics learning outcomes to support critical thinking. In order to identify and design the critical thinking framework, the objectives of this study are; 1. To highlights issues related to assessing statistical reasoning and thinking for educators instructional strategies. 2. To provide a framework for assessing statistical reasoning and thinking. 3. To develop instructional design for teaching thinking in statistics classroom. The implications for classroom teaching will be explo...
10th International Conference on Robotics, Vision, Signal Processing and Power Applications, 2019
In monitoring system using transcranial Doppler ultrasound for stroke detection, the occurrence o... more In monitoring system using transcranial Doppler ultrasound for stroke detection, the occurrence of high intensity transient signal can happen at different branch of arteries, i.e. internal cerebral artery (ICA), middle cerebral artery (MCA) and posterior cerebral artery (PCA). The representations of features can sometimes be redundant and not useful, which can degrade the classification performance. Thus, feature selection is studied and presented in this paper. The applied selection criteria are based on the unbounded Mahalanobis distance (referred as A) and single-feature-accuracy measure (referred as B). The result indicates that kinematic descriptor (SMV) is the most significant feature to predict HITS with 85.8% correct. However, the classification accuracy further improved when SMV is combined with other features in different feature subsets.
Journal of Telecommunication, Electronic and Computer Engineering, 2018
Agriculture plays a very important role in Asia economic sectors. For Malaysia, it plays a big co... more Agriculture plays a very important role in Asia economic sectors. For Malaysia, it plays a big contribution towards the country’s development. Mangifera Indica L., commonly known as Mango, is one of the fruit that has high economic demand and potential in Malaysia export business. However, due to radical climate changes from hot to humid, Mango is exposed towards a number of disease and this will affect its production. Colletotrichum gloeosporioides is one of the major diseases that could occur on any types of Mango. This fungus can attack on fruit skin and leaf, therefore a method that able to detect and control it would be much appreciated. Hence, this paper shows that the presence of Colletotrichum gloeosporioides type of pathogen can be detected by using Electronic Nose (E-Nose). The E-Nose will detect the Volatile Organic Compound (VOC) that produced from this fungus. Further analysis and justification on its existence are completed by using one of Multivariate-Statistical Anal...
International Journal of Academic Research in Business and Social Sciences
Exposure to toxic gases will affect the well-being of people in the nearby area if it is not care... more Exposure to toxic gases will affect the well-being of people in the nearby area if it is not carefully monitored. This study proposes a Wireless Electronic Nose (e-nose) System to monitor some toxic gases, temperature and humidity in the environment. The environment is monitored by using four units of wireless e-nose known as node, positioned at pre-determined locations. The node consists of toxic gases sensors as well as temperature and humidity sensor that acquired data from the environment in 30 minutes interval. The acquired data is sent wirelessly to the main node through NRF24L01 Radio Frequency (RF) transceiver. The main node transmits the data to a web of things system via Mobile Communication/General Radio Packet Service (GSM/GPRS) module. The acquired data is analysed using Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Radial Basis Function (RBF) of the Artificial Neural Network (ANN). Initial result shows that the system is able to monitor th...
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Papers by Maz Jamilah Masnan