Junita Mohamad-Saleh

University of Science Malaysia | USM · School of Electrical and Electronic Engineering

Applying optimization techniques to control systems remains a challenging task. Control system technology is emerging rapidly due to the high demands for commercialization in engineering and industrial fields, but existing optimization techniques are considered weak to cope with increasingly complex control problems. More powerful optimization tech...

Landslide is one of the natural disasters that cause property damages and human injuries. Landslide hazard predictions are crucial measures to reduce the damages and losses. One of the effective approaches in landslide prediction is landslide susceptibility analysis (LSA). In this article, LSA is carried out on the study area, Penang Island. The im...

The grasshopper optimization algorithm (GOA), inspired by the behavior of grasshopper swarms, has proven efficient in solving globally constrained optimization problems. However, the original GOA exhibits some shortcomings in that its original linear convergence parameter causes the exploration and exploitation processes to be unbalanced, leading t...

A photovoltaic (PV) system is composed of a PV panel, controller and boost converter. This review article presents a critical review, contributing to a better understanding of the interrelationship of all these internal devices in the PV system, their respective layouts, fundamental working principles, and architectural effects. The PV panel is a p...

Fusion of X-band Doppler radar and infrared sensors can offer a great advantage for close proximity time-to-collision (TTC) prediction in the field of autonomous robot navigation due to precise obstacle speed detection and direction sensing. Nevertheless, poor ranging performance from the infrared sensors may result owing to fluctuating reflectivit...

This research paper proposes a hybrid Whale Optimization Algorithm (WOA) variant based on Equilibrium Optimizer (EO), named Equilibrium Whale Optimization Algorithm (EWOA). The major finding lies in an efficient hybridization of bio-inspired (WOA) and physics-based (EO) metaheuristic algorithms. Upon mathematical modelling, EWOA proposes a main arc...

To prevent and mitigate landslide risks, landslide susceptibility is an essential tool to plan and manage urban development, especially in hilly regions. This study explores two metaheuristic-algorithms, i.e., artificial bee colony (ABC), and artificial fish swarm (AFS), for the optimization of artificial neural network (ANN) model. These two algor...

Normative Fish Swarm Algorithm (NFSA) is a novel variant of the Artificial Fish Swarm Algorithm (AFSA) proposed in 2019, and has been proven effective in solving single-objective optimization problems. Inspired by the potential of NFSA, this paper proposes an evolutionary multi-objective optimization algorithm, namely “Multi-Objective Normative Fis...

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Background: According to ASEAN Centre of Energy 2020 report, electrification rates in certain ASEAN countries are considerably low. The energy sector faces issues of unreliable supply, undersupply and high electricity rates. As power supply is an important source of daily requirement, this research work aims to improve the efficiency of solar power...

Sine Cosine Algorithm (SCA) is one of the simplest optimization algorithms and is used to solve a wide range of problems due to using two simple mathematical equations. However, it faces local optima stagnation because of the constraints in its exploration and exploitation mechanism. To solve this problem, many researchers proposed new versions of...

The Unified Power Quality Compensator (UPQC) is one of the most widely studied Custom Power Devices (CPDs) as it is a single solution for mitigating voltage and current-related abnormalities in a distribution grid, which may arise due to increased use of non-linear loads and integration of renewable energy sources. In this paper, a popular control...

Artificial fish swarm algorithm (AFSA) is a strategy which imitates the natural behavior of fish swarm in the real environment. Many improvements and modifications have been proposed on AFSA to improve its optimization performance. To date, nevertheless, the existing algorithms are still unable to achieve a satisfactory global optimum. This paper p...

This paper introduces a hybrid deep learning model which integrates particle swarm optimization (PSO) with VGG-face deep learning network for face sketch recognition problem. Particularly, the proposed hybrid model incorporates PSO into VGG-face to find the best filters of the last layer that have the highest contribution in face sketch recognition...

Modern-era largely depends on Deep Learning (DL) in a lot of applications. Medical Images Diagnosis is one of the important fields nowadays because it is related to human life. But this DL requires large datasets as well as powerful computing resources. At the beginning of 2020, the world faced a new pandemic called COVID-19. Since it is new, short...

In this paper, emerging grid synchronization techniques for power electronic converters are reviewed. In recent years, there has been a significant increase in the penetration of Distributed Generation (DG) in modern grid architecture. DGs such as solar photovoltaics, wind turbines are interfaced with the grid by way of power electronic converters....

This chapter provides a conceptual overview of Machine Learning (ML) from an Industrial Process Tomography (IPT) application viewpoint. It begins with introductory discussion on how this can be advantageously applied in IPT applications where direct on-line sensing of process information is needed. A basic foundational review compares the principle...

The standard Whale Optimization Algorithm (WOA) involves exploitation and exploration operations which require to be balanced for improved performance. This paper suggests a new enhanced WOA to improve the convergence speed and enhance the global optimum by balancing exploitation and exploration processes. New stages have been suggested at the hunt...

Sine Cosine Algorithm (SCA) was recognized as a lightweight, efficient, and has a clear math principal optimizer. However, SCA still suffers from a set of problems such as stagnation at local optima, a slow convergence curve, and a lack of efficient balancing between exploration and exploitation search modes. To mitigate these limitations and impro...

In this paper, the artificial bee colony (ABC) algorithm is used to generate landslide susceptibility maps. To the best of our knowledge, it is the first time the ABC algorithm is applied as a classifier on landslide susceptibility mapping. Twelve features are considered as inputs for the ABC model in this research work. These features contain redu...

Landslide is a natural disaster that occurs mostly in hill areas. Landslide hazard mapping is used to classify the prone areas to mitigate the risk of landslide hazards. This paper aims to compare spatial landslide prediction performance using an artificial neural network (ANN) model based on different data input configurations, different numbers o...

Landslide is one of the natural disasters in Malaysia. It causes property damages, infrastructure destruction, injuries and causalities. Landslide hazard mapping is one of the efforts to identify the landslide prone areas with the purpose of reducing the risk of landslide hazards. In this paper, landslide hazard map of the study area, Penang Island...

In this work, a binaural model resembling the human auditory system was built using a pair of three-dimensional (3D)-printed ears to localize a sound source in both vertical and horizontal directions. An analysis on the proposed model was firstly conducted to study the correlations between the spatial auditory cues and the 3D polar coordinate of th...

Among swarm-intelligence based (SI) algorithms, artificial bee colony (ABC) algorithm that is inspired by the intelligent behavior of honeybees has recently captured much interest from optimization researchers. They have come out with the proposal of ABC variants with the aims to cater the limitations’ of ABC; slow convergence speed on unimodal fun...

Simulated annealing (SA) was recognized as an effective local search optimizer, and it showed a great success in many real-world optimization problems. However, it has slow convergence rate and its performance is widely affected by the settings of its parameters, namely the annealing factor and the mutation rate. To mitigate these limitations, this...

In this paper, a swarm-based optimization algorithm, normative fish swarm algorithm (NFSA) is proposed as an effective global and local search technique to obtain effective global optima at superior convergence speed. Artificial fish swarm algorithm is a recent swarm-based algorithm that imitates the behavior of fish swarm in the real environment....

In this work, a hybrid optimization-based model is introduced to handle the problem of face sketch recognition. The proposed model comprises a total of three layers that are global search layer, control layer, and fine-tuning layer. The global layer contains a set of search operations from particle swarm optimization (PSO) algorithm to perform the...

The optimal economic operation and planning of electric grid system has always occupied a noteworthy concern in the power engineering. Constant growth in the fossil fuel production, large interconnection of the electric networks and energy crisis in the world necessitate the economic operation of dedicated power producing units. Hence, it is crucia...

The main aim of this work is to develop a component-based face sketch recognition model. The proposed model adopts an enhanced evolutionary optimizer (EEO) to perform the task of face sketched components localization. EEO is applied to an unknown input sketch to make an automatic localization for its components i.e. eyes, nose, and mouth. After tha...

Nowadays, Big Data image processing is very much in need due to its proven success in the field of business information system, medical science and social media. However, as the days are passing by, the computation of Big Data images is becoming more complex which ultimately results in complex resource management and higher task execution time. Res...

Landslide is one of the disasters which cause property damages, infrastructure destruction, injury and death. This paper presents the analysis of landslide hazard mapping of Penang Island Malaysia using bivariate statistical methods. Bivariate statistical methods are simple approach which are capable to produce good results in short computational t...

The rising complexity of real-world problems has inspired researchers to search for effective problem-solving techniques. Swarm intelligence and evolutionary computation techniques are outstanding examples that nature has been an unending source of motivation. Bio-inspired optimization algorithms stem from the major field of computational Intellige...

Multimodal benchmark function optimization has gained a growing interest exclusively in the evolutionary computation research field which involves achieving all or most of the multiple solutions contrasting a single best solution. A large number of real-world optimization problems can be considered as multimodal function optimization. Recently intr...

Optimization is an important field of research. Various optimization algorithms have been developed to solve optimization problems. Nevertheless,many have not succeeded to achieve the real global optima. Hence, a research on designing and developing a global search and optimization algorithm is presented in this paper. The aim is to enhance the per...

A hybrid algorithm for optimizing a complex power system-based problem, economic environmental dispatch (EED) is proposed. The algorithm hybridizes a recently proposed artificial bee colony (ABC) variant referred to as JA-ABC3 and a local search technique, evolutionary gradient search (EGS) which has been enhanced i.e., augmented. The enhanced EGS...

Face is one of the important parts of the human body that can be used in video surveillance security (VSS) system for identity recognition purposes. However, systems that work under uncontrolled environment such as VSS system suffer from illumination changes, unpredictability of face appearance due to the presence of accessories such as sunglasses...

Plug-in electric vehicle (PEV) has experienced major transformations since the last few decades. The success of smart electric grid with the addition of renewable energy solely depends on the extensive diffusion of PEV for a carbon-free and sustainable transport sector. Current technical studies concerning numerous optimization methods connected to...

In this paper, a novel fuzzy support vector machine (FSVM) coupled with a memetic particle swarm optimization (MPSO) algorithm is introduced. Its application to a license plate recognition problem is studied comprehensively. The proposed recognition model comprises linear FSVM classifiers which are used to locate a two-character window of the licen...

Artificial bee colony (ABC) algorithm has been widely used to solve various optimization problems due to its simplicity and flexibility besides showing outrageous results in comparison to other optimization algorithms. Nevertheless, ABC has been found to suffer from few limitations such as slow convergence rates and premature convergence tendency....

Developing an effective memetic algorithm that integrates the Particle Swarm Optimization (PSO) algorithm and a local search method is a difficult task. The challenging issues include when the local search method should be called, the frequency of calling the local search method, as well as which particle should undergo the local search operations....

This paper presents a study on optimization of a complex real-world application; economic environmental dispatch (EED) using two recently proposed modified ABC variants, named as JA-ABC3 and JA-ABC4a. EED is known to be a problem that is difficult yet crucial to be solved. Thus, robust optimization algorithms are needed to solve this kind of proble...

Parallelization of task is considered to be a huge challenge for future extreme-scale computing system. Sophisticated parallel computing system necessitates solving the bus contention in a most efficient manner with high computation rate. The major challenge to deal with is the achievement of high CPU core usage through increased task parallelism b...

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC al...

Human skin detection is an essential step in most human detection applications, such as face detection. The performance of any skin detection system depends on assessment of two components: feature extraction and detection method. Skin color is a robust cue used for human skin detection. However, the performance of color-based detection methods is...

Region of Interest (ROI) extraction is a crucial step in automatic hand vein biometric and biomedical systems. The aim of ROI extraction is to decide which part of the image is suitable for hand vein feature extraction. The majority vein patterns sometimes can be determined at different locations; left, right and centre of the back of hand. The exi...

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. Ne...

Inspired by the intelligent foraging behaviour of honeybees swarm, Artificial Bee Colony (ABC) has been introduced by Karagoba in 2005. ABC algorithm has exhibited superior performance compared to other algorithms such as Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. Despite its outstanding pe...

The prime motive of economic load dispatch (ELD) is to optimize the production cost of electrical power generation through appropriate division of load demand among online generating units. Bio-inspired optimization algorithms have outperformed classical techniques for optimizing the production cost. Probability-selection artificial bee colony (PS-...

Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications. Although many researches have been carried out for skin color detection, there is no consensus on which color space is the most appropriate for skin color detection because many researchers do not provide strict justif...

This paper presents the estimation of purity of honey using artificial neural network (ANN). ANN method was used to automate the decision of estimation, replacing the manual human approximate method. A total of 21 honey purity samples from various concentrations of pure honey, adulterated honey, and pure sugar were collected. The data were collecte...

Basically, there are two kinds of artificial neural network (ANN), which can be classified into supervised and unsupervised. Commonly, supervised neural networks are trained or weights adjusted, so that a particular input leads to a specific target output. Generally, the supervised training methods are commonly used in solving most problems. An ANN...

An induction motor is the most commonly used motor in industry today. Motor circuit parameters are essential for designing, evaluating performance, and controlling the applications of the motor. However, it is difficult to measure the electric parameters, e.g., resistance and reactance, of induction motors accurately. Therefore, researchers have no...

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeli...

As technology becomes increasingly able to meet the requirements, interest in faster, noncoherent, frequency hopping rates to reduce the jamming of communication has heightened. The focus of this paper is on the performance of the fast frequency hopping spread spectrum system operating in the presence of partial band noise jamming. In this paper we...

As technology becomes increasingly able to meet the requirements, interest in faster, noncoherent, frequency hopping rates to reduce the jamming of communication has heightened. The focus of this paper is on the performance of the fast frequency hopping spread spectrum system operating in the presence of partial band noise jamming. In this paper we...

As technology becomes increasingly able to meet the requirements, interest in faster, noncoherent, frequency hopping rates to reduce the jamming of communication has heightened. The focus of this paper is on the performance of the fast frequency hopping spread spectrum system operating in the presence of partial band noise jamming. In this paper we...

Artificial Bee Colony (ABC) applies foraging phenomenon of honeybees for evolving the optimal solutions of problems at hand. ABC algorithm is one of many prominent bioinspired optimization algorithms. Moreover, ABC algorithm is capable on inducting new possible-solutions while the algorithm searches for the optimal solutions. Scout-bee is responsib...

Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested during optimum stage for maximum oil production. This paper presents the application of color vision for automated ripeness classification of oil palm FFB. Images of oil palm FFBs of type DxP Yangambi were collected and an...

Skin color is a robust cue in human skin detection. It has been widely used in various human-related image processing applications that skin detection techniques based on skin color information have gained much attention recently. Although several techniques have been proposed, skin color detection still remains as a challenge mainly due to problem...

Artificial Bee Colony (ABC) optimization algorithm has captured much attention of researchers from various fields, in recent times. Moreover, various comparative studies clearly states dominant convergence of ABC algorithm over numerous other bio-inspired optimization algorithms. ABC optimization algorithm, its variants and hybrids have unique abil...

Artificial Bee Colony (ABC) optimization algorithm has captured much attention of researchers from various fields, in recent times. Moreover, various comparative studies clearly reports robust convergence of ABC algorithm than other bio-inspired optimization algorithms. Nevertheless, like other optimization algorithms, ABC suffers from slower conve...

This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysi...

Electric power grid is a widely distributed system, consisting of dispersed generators interconnected through transmission lines, mounting real and reactive power compensators, etc. Moreover, with deregulation and growth of the power industry, power systems elements are forced to operate very near to their maximum capacity and hence, the system bec...

This paper presents the ripeness classification of oil palm fresh fruit bunch (FFB) using artificial neural network (ANN). ANN method was used to automate the decision of grading oil plam FFBs, replacing the manual human grading method. A total of 80 oil palm FFB samples from unripe, underripe, ripe and overripe categories were collected. Images of...

This study presents a novel method for controlling the effect of outdoor illumination on object color hues by using an external white LED illumination to adapt to changing outdoor illumination. Outdoor illumination varies with shadows and cloud movements passing the sunlight. Gradual or sudden changes in illumination in outdoor applications influen...

Many flow regime classification systems based on Electrical Capacitance To-mography (ECT) sensor data have been developed, but they only focused on fixed ECT sensor parameters. Due to fixed sensor parameters, the systems are not generic because they can only work with data based on the particular ECT sensor parameters. This paper presents the work...

The paper demonstrates a method for the implementation of an olfactory system for the detection of sulfate-reducing bacteria. The unchecked growth of sulfate-reducing bacteria causes serious microbiologically-influenced corrosion problems in various industrial systems. Conventional techniques or instruments used to detect the presence of bacteria a...

Essentially, motive behind using control system is to generate suitable control signal for yielding desired response of a physical process. Control of synchronous generator has always remained very critical in power system operation and control. For certain well known reasons power generators are normally operated well below their steady state stab...

An image of hand vein acquired by near-infrared (NIR) imaging device usually suffers from low contrast and noise due to non-illumination and thickness of the hand skin. This makes subsequent processing such as segmentation difficult. In this work, combination of histogram-based and fuzzy-based contrast enhancement algorithms are applied on hand vei...

We apply noise suppression based on a feed-forward neural network (FFNN) onto hand vein images. A neural network is employed to classify corrupted and noncorrupted pixels. Filtering is only carried out on corrupted pixels, keeping the noncorrupted ones unchanged. The emphasis is on the selection of relevant inputs and training patterns. With approp...

This paper presents a method for Electrical Capacitance Tomography (ECT) flow classification using voting technique, employing Multilayer Perceptrons (MLPs) as the intelligent pattern classifiers. MLP classifiers were trained with a set of simulated ECT data associated to various flow patterns and was tested with untrained data to verify their perf...

This paper discusses the Design of Experiment (DOE) method to design an optimum Electrical Capacitance Tomography (ECT) sensor for gas-oil flows. The method has focused mainly on eliminating overshoots and undershoots in normalized ECT data. The DOE technique employed was an implementation of a 2k factorial design. ECT data based on ECT sensor para...