Puteh Saad

Universiti Malaysia Perlis | unimap · School of Computer and Communication Engineering

This paper presents a three-phase three-wire solar photovoltaic (PV) based DSTATCOM that can improve power quality problems. The solar PV system is designed based on peak-sun approach and simulated in HOMER (Hybrid Optimization Model for Electric Renewable) software. The technical and economic feasibility of different combinations of the system siz...

Hyper-threading (HT) technology allows one thread to execute its task while another thread is stalled waiting for shared resource or other operations to complete. Thus, this reduces the idle time of a processor. If HT is enabled, an operating system would see two logical cores per each physical core. This gives one physical core the ability to run...

Multicore technologies are abundant. Hyperthreading Technology is claimed to further boost performance of every single core available on a multicore platform by allowing multiple threads sharing a core resources. Even though this is true in the general case. Does the statement remains true for allkinds of code category which includes CPU, memory, I...

Directional filterbank such as contourlet become popular due its ability to capture two dimensional curves efficiently. In this work, transform with directional filterbank is tested to preserve texture information in texture images. Our initial hypothesis is that, transform with directional filter bank will be able to preserve texture information e...

This paper reviews neural network control algorithm for power quality improvement. Further, this paper focuses on the neural network control algorithm for DSTATCOM and surveys its area of improvements. Various architectures of Neural Network such as Adaline/Widrow-Hoff, perceptron, Back-propagation (BP), Hopfield, and Radial Basis Function (RBF) th...

In this paper, we present a hybrid speaker verification system based on the Hidden Markov Models (HMMs) and Vector Quantization(VQ) and Least Mean-Square (LMS) adaptive filtering. The aim of using hybrid speaker verification is to improve the HMMs performance, while LMS adaptive filtering is to improve the hybrid speaker verification performance in...

This paper evaluates the performance of Distribution Static Synchronous Compensator (DSTATCOM) using a Voltage Reference Configuration (VRC) and the Instantaneous Power Theory (PQ) control scheme for power quality improvement in three-phase three-wire distribution system. It is used for harmonic elimination according to IEEE-519 standards under non...

Breast cancer is the number one killer disease among women worldwide. Although this disease may affect women and men but the rate of incidence and number of deaths are high among women compared to men. Early detection of breast cancer helps to increase the chance of survival since early treatment can be decided for the patients who suffer from this...

A Hybrid Reconfigurable antenna is proposed in this paper. The antenna is a combination of beam steering and beam shaping RLSA antenna. The beam steering ability is prominently influenced by the feedline's spiral and radius while beam shaping's forte is depending on the 45º of the aperture slots as well as 'bridge' feed line. The spiral feed line a...

The rice husk is investigated as an absorber of RF signals produced by hybrid antennas in this research. The fabricated element plank of rice husk is placed between the feed line of the beam shaping antenna and radiating element of the beam steering antenna. Beam shaping antenna is activated by particular PIN diode switches to radiate with four wel...

The rice husk is investigated as an absorber of RF signals produced by hybrid antennas in this research. The fabricated element plank of rice husk is placed between the feed line of the beam shaping antenna and radiating element of the beam steering antenna. Beam shaping antenna is activated by particular PIN diode switches to radiate with four wel...

A Meander Line Antenna (MLA) for 2.45 GHz is proposed. This research focuses on the optimum value of gain and reflection coefficient. Therefore, the MLA's parametric studies is discussed which involved the number of turn, width of feed (W1), length of feed (LI) and vertical length partial ground (L3). As a result, the studies have significantly ach...

Amino acid propensity score is one of the earliest successful methods used in protein secondary structure prediction. However, the score performs poorly on small-sized datasets and low-identity protein sequences. Based on current in silico method, secondary structure can be predicted from local folds or local protein structure. In biology, the evol...

Living plant identification based on images of leaf is a very challenging task in the field of pattern recognition and computer vision. However, leaf classification is an important component of computerized living plant recognition. The leaf contains important information for plant species identification despite its complexity. The objective of thi...

Iris-based biometric systems identify individuals based on the characteristics of their iris, since they are proven to remain unique for a long time. An iris recognition system includes four phases, the most important of which is preprocessing in which the iris segmentation is performed. The accuracy of an iris biometric system critically depends o...

Remote protein homology detection and fold recognition refer to detection of structural homology in proteins where there are small or no similarities in the sequence. To detect protein structural classes from protein primary sequence information, homology-based methods have been developed, which can be divided to three types: discriminative classif...

This paper proposes a novel hybrid forecasting model known as GLSSVM, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM). The GMDH is used to determine the useful input variables which work as the time series forecasting for the LSSVM model. Monthly river flow data from two stations, the Sel...

Time series consists of complex nonlinear and chaotic patterns that are difficult to forecast. This paper proposes a novel hybrid forecasting model which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for the LSSVM mode...

Time series prediction is an important problem in many applications in natural science, engineering and economics. The objective of this study is to examine the flexibility of Support Vector Machine (SVM) in time series forecasting by comparing it with a multi-layer back-propagation (BP) neural network. Five well-known time series data sets are use...

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLS...

The Iris based identification systems have been noticed exceedingly, presently. In this process, the iris should be segmented from captured eye image. The low contrast between pupil and iris, usually, will harden the segmenting process and will decrease the accuracy of detecting boundary between them. In order to segment the iris more precise, we p...

Localization and responded accordingly are the most challenging and important issues in reconfigurable microstrip antenna (RMA). Hence, the challenges of combining Radio Frequency Identification (RFID) technology into the RMA are outlined. Integrating RFID into RMA is very important in wireless communication systems since the technologies have the...

In this paper, time series prediction is considered as a problem of missing value. A model for the determination of the missing time series value is presented. The hybrid model integrating autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) model is developed to solve this problem. The developed models attempts to i...

One of the difficult tasks in iris recognition is to detect the boundary between the iris region and the pupil region. This is due to the low texture contrast between them. In order to capture the degree of texture contrast between iris region and pupil region, we propose a novel algorithm that hybrid a difference function with a factor matrix. Exp...

Pin number or password that is used for authentication can be easily attacked. This limitation triggered the utilization of biometric for secured transactions. Biometrics is unique to each individual and is reliable. Among the types of biometrics being used currently, iris is the most accurate and it remains stable throughout a person's life. Howev...

A reconfigurable beam shape and broadside radiation pattern microstrip antenna is introduced in this paper. The antenna's radiating surface is designed using a radial line slot array (RLSA) arrangement, which is fed from an aperture coupled structure. This novel feeding structure for an RLSA antenna incorporates PIN diode switches which are integra...

A beam steering radial line slot array (RLSA) antenna with reconfigurable operating frequency is proposed in this paper. The RLSA antenna is fed by an aperture coupled structure, which incorporates PIN diode switches that are integrated with the feed line. It is found that the beam steering ability and reconfigurable operating frequency are greatly...

A novel adaptive Wireless-Fidelity (Wi-Fi) system is the combination of radio frequency identification (RFID) technology, programmable intelligent microcontroller development board (PIDB) and reconfigurable antenna with beam shape characteristics. The system is capable to sustain a Wi-Fi signal adaptively above its threshold level (-81dBm) within a...

A form of a novel adaptive antenna system that combines radio frequency identification (RFID) technology, programmable intelligent computer (PIC) microcontroller and reconfigurable beam steering antenna is proposed. Localization and adaptive response are the most challenging issues in smart antenna system. In this research, the localization techniq...

Currently, it is noticed that users tend to choose shorter password as their authentication which can be easily attacked. Biometric technologies such as fingerprint scanning, voice authentication, face recognition, signature, hand geometry and iris recognition is now playing an important role especially in application related to security issue. In...

Many studies have demonstrated that combining forecasts improves accuracy relative to individual forecasts. In this paper, the combing forecasts is used to improve on individual forecasts is investigated. A combining approach based on the modified Group Method Data Handling (GMDH) method and genetic algorithm (GA), is called as the GAGMDH model is...

The task of presenting an optimal personalized learning path in an educational hypermedia system requires much effort and cost particularly in defining rules for the adaptation of learning materials. This research focuses on the adaptive course sequencing method that uses soft computing techniques as an alternative to a rule-based adaptation for an...

The iris localization is a very important step for iris-recognition. In this step concentric circular outer boundaries of the iris and the pupil in eye's image identify. We enhanced Daugman method to locate the iris by using an Average Square Shrinking Approach. The algorithm is tested using iris images from CASIA database and MMU database. The cir...

Advancements in technology have led to a paradigm shift fromtraditional to personalized learning methods with varied implementationstrategies. Presenting an optimal personalized learning path in aneducational hypermedia system is one of the strategies that is important inorder to increase the effectiveness of a learning session for each student.How...

Clinical Risk Groups (CRGs) are a clinical model in which each individual is assigned to a single mutually exclusive risk group which relates the historical clinical and demographic characteristics of individuals to the amount and type of resources that individual will consume in the future [1]. CRGs based risk adjustment system is a potential risk...

In this paper, the circular Hough transform (CHT) and the chord intersection have been used to find the circular object in the feature extraction process. The chord intersection technique does not require any gradient information which may be sensitive to noise meanwhile for the CHT technique, the gradient information has been used. In this researc...

In this paper, the circular Hough transform (CHT) and the chord intersection have been used to find the circular object in the feature extraction process. The chord intersection technique does not require any gradient information which may be sensitive to noise meanwhile for the CHT technique, the gradient information has been used. In this researc...

This paper examines the generalization characteristic of Gaussian ARTMAP (GAM) neural network in classification tasks. GAM performance for classification during training and testing is evaluated using the k-folds cross validation technique. A comparison is also done between GAM and Fuzzy ARTMAP (FAM) neural network. It is found that GAM performs be...

In this paper, a computational model has been developed to identify a face of an unknown person’s by utilizing eigenfaces as unique features and backpropagation Neural Network for recognition. The features of a basic human face are extracted using eigenfaces. These features are then used to identify an unknown face by using multiple numbers of back...

In this paper we have introduced a set of equation known as Invariant Error Computation (IEC) that is used to examine directly the invariant performance properties of moment invariant techniques. This brand new technique consists of a set of useful equations known as Total Percentage Min Absolute Error (TPMAE), Percentage Min Absolute Error 1 (PMAE...

The main objective of this research is to develop a practical system for binary image classification using Krawtchouk Moment Invariant (KMI) as the feature extraction technique while Gaussian ARTMAP (GAM) is adopted for classification task. Fundamentally, KMI is introduced by P.T. Yap back in 2003 based on the discrete orthogonal function which is...

In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an un...

Geometric moment invariant produces a set of feature vectors that are invariant under shifting, scaling and rotation. The technique is widely used to extract the global features for pattern recognition due to its discrimination power and robustness. In this paper, moment invariant is used to identify the object from the captured image using the fir...

ABSRACT In this paper a set of equation known as Invariant Error Computation (IEC) is introduced that is used to examine directly the invariant performance properties of moment invariant techniques. The technique consists of a set of equations known as Total Percentage Min Absolute Error (TPMAE), Percentage Min Absolute Error 1 (PMAE1), Percentage...

In this study we propose a new system to detect the object from an input image. The proposed system first uses the separability filter proposed by Fukui and Yamaguchi (Trans. IEICE Japan J80-D-II. 8, 2170-2177, 1997) to obtain the best object candidates and next, the system uses the circular Hough transform (CHT) to detect the presence of circular...

Object recognition is an essential routine in our daily lives. Our eyes act as a camera to capture the object and sending it to the brain to be recognized. The eye vision system inspires researchers to create machine vision systems. The camera is used to capture the object, an image processing component will then highlight the required object and a...

Curse of dimensionality is a phenomenon that will degrade the performance of Backpropagation Algorithm. This situation occurs due to the reason that there are a large number of variables associated with the data. In such situations it is likely that subsets of variables are highly correlated with each other. Therefore the accuracy and reliability o...

In this paper, we review researches on human faces from aspect of face recognition and face detection. Face emotion recognition are also reviewed. The study of human faces has much assistance on computer vision and machine learning research. We can identify the age, gender, and ethnic origin from faces. Face recognition systems are divided into the...

Non-destructive detection method is vital in quality, safety and integrity assurance during postharvest of fruits and vegetables. Mango pulp and seed weevil creates tunnel into flesh or seed of mangoes but does not shows any sign of infestation from outer skin layer, making mangoes unfit to eat. This study aimed to compare between x-ray and magneti...

The purpose of automated image classification is to facilitate a machine to classify image patterns without human intervention. There are a variety of approaches proposed to perform the task. In our case, the image chosen is that of trademark. Geometric and Zernike Moment techniques are employed to extract a set of patterns in terms of feature vect...

Recently, Malaysia is fast moving towards other new emerging businesses, technologies and industries such as the automobile sector, telecommunication and biotechnology industry. Nevertheless, Malaysia has never undermine the importance of the countries first and foremost bread winner for the country; agriculture. In agriculture, it is always import...

In the first chapter, entitled “Enhancement of Support Vector Machines for Remote Protein Homology Detection and Fold Recognition,” M. Hilmi Muda, Puteh Saad and Razib M. Othman present a comprehensive method based on two-layer multiclass classifiers. The first layer is used to detect up to superfamily and family in SCOP hierarchy, by using optimiz...

Back Propagation algorithm(BP} has been popularly used to solve various problems, however it is shrouded with the problems of low convergence and instability. In recent years, improvements have been attempted to overcome the discrepancies aforementioned. In this study, we examine the performance of four enhanced BP algorithms to predict rice yield...

Rice farming is somewhat sentimental and many of the hard facts that intertwined with the complexity of farming are often taken for granted. The interrelationship of water use in the soil-crop-atmosphere with respect to the farming practices, the availability and economic of water, the input cost and the profitability on rice production are attribu...

The critical step in automatic trademark matching is to extract trademark features from the database automatically and reliably. However, the performance of existing algorithms rely heavily on the size of the database. It is essential to incorporate an eficient classification technique to partition the database in order to ensure the performance of...

Rough set theory (RS), introduced by Zdzislaw Pawlak in the early 1980s, is a methodology that concerned with the classificatory analysis of imprecise, uncertain or incomplete information or knowledge expressed in terms of data acquired from experiences or observations. It has the ability to distinguish between object and reason about the objects i...

Timetable planning can be modelled as a constraint-satisfaction problem, and may be solved by various approaches, including genetic algorithms. An optimal solution for a timetable planning problem is difficult to find using genetic algorithms, due to the ambiguity in deciding the fitness function. Various approaches aimed at finding optimal solutio...

Nondestructive detection method is vital in quality, safety and integrity assurance during fruits and vegetables post harvest. X-ray imaging technology has been proven to be one of the successful nondestructive methods ever to be applied in detecting diseases and defects in agricultural products. In this research, infested Harum Manis mango fruits...

Iris is a desirable biometric representation of an individual for security-related applications. However the iris segmentation and normalization process is challenging due to the presence of eye lashes that occlude the iris, the dilation of pupils due to different light illumination and several other uncontrolled factors. In this work, we enhanced...

We develop a technique to identify an unknown person in a face image by using template matching and neural network classifier. The technique is separated into three main steps namely; preprocessing, feature extraction and recognition. In the preprocessing step, we process and normalize the input image using approaches proposed by Kawaguchi et al. [...

The automatic identification can be provide with extract the unique feature or characters that possessed by the individual. These unique feature or characteristic is extracted of physiological and behavior of person. The most reliable biometric identification system is iris recognition. Most commercial iris recognition systems use patented algorith...