Ahamad Tajudin Khader

Ahamad Tajudin Khader
Universiti Sains Malaysia | USM · School of Computer Science

About

187
Publications
142,649
Reads
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6,236
Citations
Citations since 2017
72 Research Items
5230 Citations
201720182019202020212022202302004006008001,0001,200
201720182019202020212022202302004006008001,0001,200
201720182019202020212022202302004006008001,0001,200
201720182019202020212022202302004006008001,0001,200

Publications

Publications (187)
Article
The electroencephalogram (EEG) signal denoising problem has been considered a challenging task because of several artifact noises, such as eye blinking, eye movement, muscle activity, and power line interference, which can corrupt the original EEG signal during the recording time. Therefore, to remove these noises, the EEG signals must be processed...
Article
Full-text available
The electroencephalogram (EEG) signal denoising problem has been considered a challenging task because of several artifact noises, such as eye blinking, eye movement, muscle activity, and power line interference, which can corrupt the original EEG signal during the recording time. Therefore, to remove these noises, the EEG signals must be processed...
Article
Full-text available
To improve the optimization efficiency for different optimization problems and take advantage of the dynamic membrane computing framework, this paper proposes an improved bat algorithm, namely, Dynamic Membrane-driven Bat Algorithm (DMBA). The dynamic construction of the DMBA algorithm aims at enhancing population diversity by balancing the explora...
Chapter
Recently, electroencephalogram (EEG) signal provides great potential for identification systems. Many studies have shown that the EEG introduces unique, universal features and natural robustness for spoofing attacks. The EEG represents a graphic recording of the electrical activity of the brain that can be measured by placing sensors (electrodes) a...
Chapter
Recently, the researchers’ attention became more interest in partitioning particular sets of documents into various subsets, due to the massive number of documents that make pattern recognition, information retrieval, and text mining more complicated. This problem is known as a text clustering problem (TCD). Several metaheuristic optimization algor...
Article
Full-text available
The power scheduling problem in a smart home (PSPSH) refers to the timely scheduling operations of smart home appliances under a set of restrictions and a dynamic pricing scheme(s) produced by a power supplier company (PSC). The primary objectives of PSPSH are: (I) minimizing the cost of the power consumed by home appliances, which refers to electr...
Article
Full-text available
For text document clustering (TDC), a novel hybrid of the multi-verse optimizer (MVO) algorithm and k-means (also called H-MVO) are proposed in this work. Moreover, a new ensemble method for an automatic topic extraction (TE) has been proposed in this paper, from a set of scientific publications in the form of text documents with the purpose of ext...
Chapter
Full-text available
Text Feature Selection (FS) is a significant step in text clustering (TC). Machine learning applications eliminate unnecessary features in order to enhance learning effectiveness. This work proposes a binary grey wolf optimizer (BGWO) algorithm to tackle the text FS problem. This method introduces a new implementation of the GWO algorithm by select...
Chapter
Full-text available
Scheduling operations of smart home appliances using an electricity pricing scheme is the primary issue facing power supplier companies and their users, due to the scheduling efficiency in maintaining power system and reducing electricity bill (EB) for users. This problem is known as power scheduling problem in a smart home (PSPSH). PSPSH can be ad...
Article
Full-text available
The automatic topic extraction (TE) from scientific publications provides a very compact summary of the clusters’ contents. This often helps in locating information easily. TE enables us to define the boundaries of the scientific fields. Text Document Clustering (TDC) represents, in general, the first step of topic identification to identify the do...
Article
Full-text available
Text clustering has been widely utilized with the aim of partitioning specific document collection into different subsets using homogeneity/heterogeneity criteria. It has also become a very complicated area of research, including pattern recognition, information retrieval, and text mining. Metaheuristics are typically used as efficient approaches f...
Article
Full-text available
In this study, a multi-verse optimizer (MVO) is utilised for the text document clus- tering (TDC) problem. TDC is treated as a discrete optimization problem, and an objective function based on the Euclidean distance is applied as similarity measure. TDC is tackled by the division of the documents into clusters; documents belonging to the same clust...
Article
Recently, electroencephalogram (EEG) signal presents a great potential for a new biometric system to deal with a cognitive task. Several studies defined the EEG with uniqueness features, universality, and natural robustness that can be used as a new track to prevent spoofing attacks. The EEG signals are the graphical recording of the brain electric...
Article
Full-text available
Background. The most common and successful technique for signal denoising with non-stationary signals, such as electroencephalogram (EEG) and electrocardiogram (ECG) is the wavelet transform (WT). The success of WT depends on the optimal configuration of its control parameters which are often experimentally set. Fortunately, the optimality of the c...
Article
Text document clustering (TDC) represents a key task in text mining and unsupervised machine learning, which partitions a specific documents' collection into varied K-groups according to certain similarity/dissimilarity criterion. There exists a considerable amount of knowledge in the text clustering field and many attempts were carried out to reso...
Article
Optimizing the power demand for smart home appliances in a smart grid is the primary challenge faced by power supplier companies, particularly during peak periods, due to its considerable effect on the stability of a power system. Therefore, power supplier companies have introduced dynamic pricing schemes that provide different prices for a time ho...
Article
Full-text available
In this paper, the multi-objective grey wolf optimiser is utilised for the power scheduling problem (PSP). The grey wolf optimiser (GWO) is a recent swarm-based optimisation algorithm tailored for various optimisation problems. PSP is addressed by scheduling home appliances to a certain time horizon to minimise the electricity bill and peak-to-aver...
Article
Full-text available
Cuckoo search algorithm (CSA) is considered one of the promising metaheuristic algorithms applied to solve numerous problems in different fields. Although it employed the Levy flight to guide the search process. But, it has drawbacks, such as utilization of global search; in certain cases, this technique may surround local optima. Also, the results...
Conference Paper
Full-text available
Feature selection is regarded as an important task in data mining. The applications of machine learning eliminate irrelevantly, redundant features so that the learning performance is improved. A novel feature selection method for unsupervised text clustering, that is, binary multi-verse optimizer algorithm (BMVO) is proposed in this paper. A new ap...
Conference Paper
Full-text available
Power Scheduling Problem (PSP) is a problem of schedule the smart home appliances at the appropriate time period according to an electricity pricing scheme. The smart home appliances can be scheduled by shifting their time operations from period to another. The significant objective of the scheduling process is to reduce the electricity bill and Pe...
Chapter
Full-text available
For the purpose of improving the search strategy of the krill herd algorithm (KHA) , an improved robust approach is proposed to address the function optimization problems, namely, modified krill herd algorithm (MKHA) . In MKHA method, the modification of krill herd algorithm focuses on genetic operators (GOs) and it occurs in the ordering of proced...
Chapter
University Examination Timetabling Problem (UETP) is a computationally complex scheduling problem. Visual Analytics (VA) is a modern visualization supported with automated processing method. The major impulse of the method lies in its ability to integrate the key component of scientific visualization and search based heuristics in the same optimiza...
Article
The diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. Q-ball imaging (QBI) is a diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fibre orientations in MRI (i.e., fibre crossing) based...
Article
The diffusion-weighted magnetic resonance imaging (DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. Q-ball imaging (QBI) is a diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fibre orientations in MRI (i.e., fibre crossing) based...
Article
Full-text available
In the modern life, the authentication technique for any system is considered as one of the most important and challenging tasks. Therefore, many researchers have developed traditional authentication systems to deal with our digital society. Recently, several studies showed that the brain electrical activity or electroencephalogram (EEG) signals co...
Article
Full-text available
In the modern life, the authentication technique for any system is considered as one of the most important challenges task which must careful consideration. Therefore, many researchers have developed traditional authentication systems to deal with our digital world. Recently, The Biometric techniques have been successfully provided a high level of...
Article
Full-text available
In this paper, a novel text clustering method, improved krill herd algorithm with a hybrid function, called MMKHA, is proposed as an efficient clustering way to obtain promising and precise results in this domain. Krill herd is a new swarm-based optimization algorithm that imitates the behavior of a group of live krill. The potential of this algori...
Article
Full-text available
This paper proposed a new gene selection method based on modified Minimum Redundancy Maximum Relevancy (MRMR) as a filtering approach and hybrid bat algorithm with β-hill climbing as an efficient wrapper approach. The gene selection is a process of selecting the discriminative genes that aid in the development of efficient cancer diagnosis and clas...
Conference Paper
Full-text available
In this paper, Grey Wolf Optimizer (GWO) is adapted for Power Scheduling Problem (PSP) of Smart Home with Smart Battery. GWO is the recent metaheuristic swarm-based optimization method stemmed by grey pack behavior in hunting process. It has been successfully tailored to a wide variety of real-world optimization problems. PSP is tackled by scheduli...
Article
Background: Cuckoo Search Algorithm (CSA) was introduced by Yang and Deb in 2009. It considers as one of the most successful in various fields compared with the metaheuristic algorithms. However, random selection is used in the original CSA which means there is no a high chance for the best solution to selected, also, losing the diversity. Discuss...
Poster
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http://www.bigdatasummit2.usm.my/
Poster
Full-text available
Recently, electroencephalogram (EEG) signal present a great potential for a new biometric system. Several studies showed that EEG presents uniqueness features, universality, and natural robustness to spoofing attacks. The EEG signals represent the graphical recording of the brain electrical activity which can be measured by placing electrodes (sens...
Article
Full-text available
Background: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to manage a large amount of text information into a subset of comparable and coherent clusters. Aims:...
Conference Paper
Full-text available
Since past three decades, the world is transformed into digital society, where every individual is living with a unique digital identifier. The main purpose of this identifier is to distinguish from others as well as to deal with digital machines which are surrounding the world. Recently, many researchers proved that the brain electrical activity o...
Article
Full-text available
Pedestrian movement in normal and panic situation has become the most outstanding research in this recent era for predictive aftermath outcome. The pedestrian movement usually will be in the self-organizing state that involves the microscopic movement based on the basic Cellular Automata (CA) model. However, during the simulation of pedestrian move...
Article
Full-text available
Cuckoo search algorithm is considered one of the promising metaheuristic algorithms applied to solve numerous problems in different fields. However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimiz...
Article
Cuckoo search algorithm is considered one of the promising metaheuristic algorithms applied to solve numerous problems in different fields. However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimiz...
Article
Krill herd (KH) algorithm is a novel swarm-based optimization algorithm that imitates krill herding behavior during the searching for foods. It has been successfully used in solving many complex optimization problems. The potency of this algorithm is very high because of its superior performance compared with other optimization algorithms. Hence, t...
Article
Full-text available
In this paper, the update process of harmony search (HS) algorithm is modified to improve its concept of diversity. The update process in HS is based on a greedy mechanism in which the new harmony solution, created in each generation, replaces the worst individual in the population, if better. This greedy process could be improved with other update...
Conference Paper
Full-text available
Since the past decades, the world has been transformed into a digital society, where every individual is living with a unique identifier. The primary purpose of this id is to distinguish from others and to deal with digital machines which are surrounding the world. Recently, many researchers showed that the brain electrical activity or electroencep...
Article
Master River Multiple Creeks Intelligent Water Drops (MRMC-IWD) is an ensemble model of the intelligent water Drop, whereby a divide-and-conquer strategy is utilized to improve the search process. In this paper, the potential of the MRMC-IWD using real-world optimization problems related to feature selection and classification tasks is assessed. An...
Chapter
Full-text available
The flower pollination algorithm (FPA) is a nature-inspired algorithm that imitates the pollination behavior of flowering plants. Optimal plant reproduction strategy involves the survival of the fittest as well as the optimal reproduction of plants in terms of numbers. These factors represent the fundamentals of the FPA and are optimization-oriente...
Chapter
Full-text available
Text clustering is an efficient analysis technique used in the domain of the text mining to arrange a huge of unorganized text documents into a subset of coherent clusters. Where, the similar documents in the same cluster. In this paper, we proposed a novel term weighting scheme, namely, length feature weight (LFW), to improve the text document clu...
Article
Full-text available
This paper introduces βHCWT, a hybrid of the β-hill climbing metaheuristic algorithm and wavelet transform (WT), as a new method for denoising electrocardiogram (ECG) signals. ECG signals are non-stationary signals that provide a graphical measure of electrical activities in human heart muscles. However, given their non-stationarity, these signals...
Article
Full-text available
The text clustering technique is an appropriate method used to partition a huge amount of text documents into groups. The documents size affects the text clustering by decreasing its performance. Subsequently, text documents contain sparse and uninformative features, which reduce the performance of the underlying text clustering algorithm and incre...
Conference Paper
Full-text available
In this paper, various mother wavelet functions are proposed for ElectroEncephaloGram (EEG) signal denoising problem. EEG is a graphical measuring of the brain electrical activity which is recording from the scalp. It represents the voltage fluctuations resulting from ionic current flows within the neurons of the brain. During recording time, there...
Conference Paper
Full-text available
In this paper, hybridization between β-hill climbing algorithm and wavelet transform (WT) are proposed for Electro Encephalo Gram (EEG) signal denoising problem. EEG is a graphical measurement for the brain electrical activity which is recording from the scalp. It represents the voltage fluctuations resulting from ionic current flows within the neu...
Article
The large amount of text information on the Internet and in modern applications makes dealing with this volume of information complicated. The text clustering technique is an appropriate tool to deal with an enormous amount of text documents by grouping these documents into coherent groups. The document size decreases the effectiveness of the text...
Presentation
Full-text available
Since past three decades, the world has been transformed into a digital society, where every individual is living with a unique digital identifier. The purpose of digital identifier is to distinguish one from the other as well as to deal with digital machines which are surrounding the world. Simultaneously, the security level is the most important...
Poster
Full-text available
Since past three decades, the world has been transformed into a digital society, where every individual is living with a unique digital identifier. The purpose of digital identifier is to distinguish one from the other as well as to deal with digital machines which are surrounding the world. Simultaneously, the security level is the most important...
Article
Full-text available
The microarray technology facilitates biologist in monitoring the activity of thousands of genes (features) in one experiment. This technology generates gene expression data, which are significantly applicable for cancer classification. However, gene expression data consider as high- dimensional data which consists of irrelevant, redundant, and noi...
Conference Paper
In this paper, modified cuckoo search algorithm (MCSA) is presented for solving global optimization problems. Cuckoo Search Algorithm (CSA) was proposed by Yang and Deb in 2009. To date, work on this algorithm has significantly increased, and the CSA has succeeded in having its rightful place among other optimization methodologies. The modified ver...
Conference Paper
Full-text available
Regarding the increasing volume of document information (text) on Internet network pages, recent applications, and so on, the dealing with this knowledge has become incredibly complex because of the size. The text clustering is a proper technique used to arrange a tremendous amount of text information by classifying into a subset of clusters. In th...
Article
Full-text available
This paper proposes a hybrid harmony search algorithm (HHSA) for solving the highly constrained nurse rostering problem (NRP). The NRP is a combinatorial optimization problem tackled by assigning a set of shifts to a set of nurses; each has specific skills and work contract, to a predefined rostering period according to a set of constraints. The ha...