In recent years, many classification models have been developed and applied to increase their accuracy. The concept of distance between two samples or two variables is a fundamental concept in multivariate analysis. This paper proposed a tool that used different similarity distance approaches with ranking method based on Mean Average Precision (MAP). In this study, several similarity distance methods were used, such as Euclidean, Manhattan, Chebyshev, Sorenson and Cosine. The most suitable distance measure was based on the smallest value of distance between the samples. However, the real solution showed that the results were not accurate as and thus, MAP was considered the best approach to overcome current limitations.
Many nonlinear problems that arise in various science and engineering fields can be
modelled by the Goursat partial differential equations. Modelling these non-linear
problems using the Goursat partial differential equations has not received much
attention especially the theoretical aspect . The proposed scheme of solution is
supported by examining a nonlinear Goursat problem. The verification of the
theoretical results from several series of numerical experiments are discussed. Results
obtained from Taylor series expansion show that the proposed new scheme is
consistent. By using the von Neumann analysis and essence of stability, the proposed
new scheme is found to be unconditionally stable. In addition, the trend of the
numerical results shows that the new scheme is also convergent.
Iris recognition has become a widely popular biometric system. The stable textures and features of the human iris have made such biometric systems efficient and accurate for purposes of verification and identification. The term non-ideal iris refers to a situation in which the iris is occluded by noise, including reflections, eyelashes, eyelids and so on. Most current iris recognition algorithms assume that the iris is not occluded, which is less accurate. A method using only some parts of the iris may be suitable to deal with a non-ideal iris. The current application of iris recognition systems are plagued by weaknesses such as slow processing times, especially when dealing with many irises. In this study, a sub-iris recognition technique is proposed to deal with the non-ideal iris, while reducing execution time via an embedded system using a graphical processing unit (GPU). The experiment revealed that the proposed method was accurate and fast.
Space Vector Pulse Width Modulation (SVPWM) method is widely used as a modulation technique
to drive a three-phase inverter. It is an advanced computational intensive method used in pulse width modulation (PWM) algorithm for the three-phase voltage source inverter. Compared with the other PWM techniques, SVPWM is easier to implement, thus, it is the most preferred technique among others. Mathematical model for SVPWM was developed using MATLAB/ Simulink software. In this paper, the interface between MATLAB Simulink with the three-phase inverter by using Arduino Uno microcontroller is proposed. Arduino Uno generates the SVPWM signals for Permanent Magnet Synchronous Motor (PMSM) and is described in this paper. This work consists of software and hardware implementations. Simulation was done via Matlab/Simulink software to verify the effectiveness of the system and to measure the percentage of Total Harmonic Distortion (THD). The results show that SVPWM technique is able to drive the three-phase inverter with the Arduino UNO.
In an earlier study, a three-fingered robot hand was developed for assembly work. Proportional Integral Derivative (PID) control was used to control the position of a DC micromotor measured by an encoder. However, PID control alone could not cater the nonlinearities due to friction of gears and varying loads applied to the finger. Therefore, in order to develop an intelligent control algorithm in future, the effects of varying PID gains need to be investigated to distinguish the optimal value that could produce the best transient response performance. This paper discusses the effect of varying PID gains on position transient response of the joint motor of robot hand through real-time experiments. Several ranges of KP, KI and KD were identified based on the required transient response parameters such as percentage overshoot (%OS), settling time (TS) of within 2%, steady state error (SSE) and rise time (TR). The gains are tuned across the range by a fixed interval with the tuning order starting from KP, KI and KD. It can be observed that the suitable ranges of PID are 0.3 to 0.5 for KP, 1.15 to 1.45 for KI and 0.10 to 0.14 for KD. Meanwhile, the optimum value of 0.4, 1.45 and 0.10 for KP, KI and KD respectively is found to produce 0 of % OS, 5.09 sec of TS and 2.48 sec of TR. Hence, the gains can be applied to the development of an improved position control using intelligent method for the robot hand in future works.
Transferring a huge amount of data between different network locations over the network links depends on the network's traffic capacity and data rate. Traditionally, a mobile device may be moved to achieve the operations of vertical handover, considering only one criterion, that is the Received Signal Strength (RSS). The use of a single criterion may cause service interruption, an unbalanced network load and an inefficient vertical handover. In this paper, we propose an enhanced vertical handover decision algorithm based on multiple criteria in the heterogeneous wireless network. The algorithm consists of three technology interfaces: Long-Term Evolution (LTE), Worldwide interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. The simulation results illustrate that the three types of decision algorithms outperform the traditional network decision algorithm in terms of handover number probability and the handover failure probability. In addition, it is noticed that the network priority handover decision algorithm produces better results compared to the equal priority and the mobile priority handover decision algorithm. Finally, the simulation results are validated by the analytical model.
Combinatorial test design is a plan of test that aims to reduce the amount of test cases systematically by choosing a subset of the test cases based on the combination of input variables. The subset covers all possible combinations of a given strength and hence tries to match the effectiveness of the exhaustive set. This mechanism of reduction has been used successfully in software testing research with t-way testing (where t indicates the interaction strength of combinations). Potentially, other systems may exhibit many similarities with this approach. Hence, it could form an emerging application in different areas of research due to its usefulness. To this end, more recently it has been applied in a few research areas successfully. In this paper, we explore the applicability of combinatorial test design technique for Fractional Order (FO), Proportional-Integral-Derivative (PID) parameter design controller, named as FOPID, for an automatic voltage regulator (AVR) system. Throughout the paper, we justify this new application theoretically and practically through simulations. In addition, we report on first experiments indicating its practical use in this field. We design different algorithms and adapted other strategies to cover all the combinations with an optimum and effective test set. Our findings indicate that combinatorial test design can find the combinations that lead to optimum design. Besides this, we also found that by increasing the strength of combination, we can approach to the optimum design in a way that with only 4-way combinatorial set, we can get the effectiveness of an exhaustive test set. This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly.
This paper describes an approach for improving the accuracy of memory-based collaborative filtering, based on the technique for order of preference by similarity to ideal solution (TOPSIS) method. Recommender systems are used to filter the huge amount of data available online based on user-defined preferences. Collaborative filtering (CF) is a commonly used recommendation approach that generates recommendations based on correlations among user preferences. Although several enhancements have increased the accuracy of memory-based CF through the development of improved similarity measures for finding successful neighbors, there has been less investigation into prediction score methods, in which rating/preference scores are assigned to items that have not yet been selected by a user. A TOPSIS solution for evaluating multiple alternatives based on more than one criterion is proposed as an alternative to prediction score methods for evaluating and ranking items based on the results from similar users. The recommendation accuracy of the proposed TOPSIS technique is evaluated by applying it to various common CF baseline methods, which are then used to analyze the MovieLens 100K and 1M benchmark datasets. The results show that CF based on the TOPSIS method is more accurate than baseline CF methods across a number of common evaluation metrics.
The presence of motion artefacts in ECG signals can cause misleading interpretation of cardiovascular status. Recently, reducing the motion artefact from ECG signal has gained the interest of many researchers. Due to the overlapping nature of the motion artefact with the ECG signal, it is difficult to reduce motion artefact without distorting the original ECG signal. However, the application of an adaptive noise canceler has shown that it is effective in reducing motion artefacts if the appropriate noise reference that is correlated with the noise in the ECG signal is available. Unfortunately, the noise reference is not always correlated with motion artefact. Consequently, filtering with such a noise reference may lead to contaminating the ECG signal. In this paper, a two-stage filtering motion artefact reduction algorithm is proposed. In the algorithm, two methods are proposed, each of which works in one stage. The weighted adaptive noise filtering method (WAF) is proposed for the first stage. The acceleration derivative is used as motion artefact reference and the Pearson correlation coefficient between acceleration and ECG signal is used as a weighting factor. In the second stage, a recursive Hampel filter-based estimation method (RHFBE) is proposed for estimating the ECG signal segments, based on the spatial correlation of the ECG segment component that is obtained from successive ECG signals. Real-World dataset is used to evaluate the effectiveness of the proposed methods compared to the conventional adaptive filter. The results show a promising enhancement in terms of reducing motion artefacts from the ECG signals recorded by a cost-effective single lead ECG sensor during several activities of different subjects.
This paper presents a new method for a vibration-based piezoelectric energy harvesting system using a backtracking search algorithm (BSA)-based proportional-integral (PI) voltage controller. This technique eliminates the exhaustive conventional trial-and-error procedure for obtaining optimized parameter values of proportional gain (Kp), and integral gain (Ki) for PI voltage controllers. The generated estimate values of Kp and Ki are executed in the PI voltage controller that is developed through the BSA optimization technique. In this study, mean absolute error (MAE) is used as an objective function to minimize output error for a piezoelectric energy harvesting system (PEHS). The model for the PEHS is designed and analyzed using the BSA optimization technique. The BSA-based PI voltage controller of the PEHS produces a significant improvement in minimizing the output error of the converter and a robust, regulated pulse-width modulation (PWM) signal to convert a MOSFET switch, with the best response in terms of rise time and settling time under various load conditions.
In this paper we present a new line search method known as the HBFGS method, which uses the search direction of the conjugate gradient method with the quasi-Newton updates. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) update is used as approximation of the Hessian for the methods. The new algorithm is compared with the BFGS method in terms of iteration counts and CPU-time. Our numerical analysis provides strong evidence that the proposed HBFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent.
In this paper, an improved trigonometrically fitted zero-dissipative explicit two-step hybrid method with fifth algebraic
order is derived. The method is applied to several problems where by the solutions are oscillatory in nature. Numerical
results obtained are compared with existing methods in the scientific literature. The comparison shows that the new
method is more effective and efficient than the existing methods of the same order.
Time stepping algorithm with spatial parallelisation is commonly used to solve time dependent partial differential equations. Computation in each time step is carried out using all processors available before sequentially advancing to the next time step. In cases where few spatial components are involved and there are relatively many processors available for use, this will result in fine granularity and decreased scalability. Naturally one alternative is to parallelise the temporal domain. Several time parallelisation algorithms have been suggested for the past two decades. One of them is the pipelined iterations across time steps. In this pipelined time stepping method, communication however is extensive between time steps during the pipelining process. This causes a decrease in performance on distributed memory environment which often has high message latency. We present a modified pipelined time stepping algorithm based on delayed pipelining and reduced communication strategies to improve overall execution time on a distributed memory environment using MPI. Our goal is to reduce the inter-time step communications while providing adequate information for the next time step to converge. Numerical result confirms that the improved algorithm is faster than the original pipelined algorithm and sequential time stepping algorithm with spatial parallelisation alone. The improved algorithm is most beneficial for fine granularity time dependent problems with limited spatial parallelisation.
The discretization of the second-order linear self-adjoint ellliptic partial differential equation problem subject to periodic boundary conditions results in a system of linear equations of the form Mu = s, where M is a block cyclic tridiagonal square matric. In this paper, the relationship between the spectral radius and overrelaxation factor for the problem is derived.
Pendiskretan masalah persamaan pembeza separa (PPS) eliptik swadampingan linear peringkat kedua menghasilkan satu sistem persamaan linear bentuk Mu = s, dengan M merupakan satu matriks segiempatsama tiga pepenjuru berkitar blok. Dalam kertas ini, hubungan di antara jejari spektrum dan faktor pengenduran berlebihan untuk masalah itu akan dirumuskan.
The key concerns to enhance the lifetime of IoT-enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are energy-efficiency and reliable data delivery under constrained resource. Traditional transmission approaches increase the communication overhead, which results in congestion and affect the reliable data delivery. Currently, many routing protocols have been proposed for UWSNs to ensure reliable data delivery and to conserve the node's battery with minimum communication overhead (by avoiding void holes in the network). In this paper, adaptive energy-efficient routing protocols are proposed to tackle the aforementioned problems using the Shortest Path First (SPF) with least number of active nodes strategy. These novel protocols have been developed by integrating the prominent features of Forward Layered Multi-path Power Control One (FLMPC-One) routing protocol, which uses 2-hop neighbor information, Forward Layered Multi-path Power Control Two (FLMPC-Two) routing protocol, which uses 3-hop neighbor information and 'Dijkstra' algorithm (for shortest path selection). Different Packet Sizes (PSs) with different Data Rates (DRs) are also taken into consideration to check the dynamicity of the proposed protocols. The achieved outcomes clearly validate the proposed protocols, namely: Shortest Path First using 3-hop neighbors information (SPF-Three) and Breadth First Search with Shortest Path First using 3-hop neighbors information (BFS-SPF-Three). Simulation results show the effectiveness of the proposed protocols in terms of minimum Energy Consumption (EC) and Required Packet Error Rate (RPER) with a minimum number of active nodes at the cost of affordable delay.
In this study, we developed a method for directly determining the energy deposited over the entire energy range by monitoring the light output from a plastic scintillator under gamma irradiation. The relative light output was analyzed based on Birks' semi-empirical formula for ionization to obtain the quenching parameter as kB = 0.016 ± 0.0004 g cm-2 MeV-1. Comparisons of experimental and calculated results for the light output spectra showed that considering the quenching effect, background subtraction, source casing, and energy sampling were essential for achieving good agreement.
In this study, a novel matrix method based on collocation points is proposed to solve some linear and nonlinear integro-differential equations with variable coefficients under the mixed conditions. The solutions are obtained by means of Dickson and Taylor polynomials. The presented method transforms the equation and its conditions into matrix equations which comply with a system of linear algebraic equations with unknown Dickson coefficients, via collocation points in a finite interval. While solving the matrix equation, the Dickson coefficients and the polynomial approximation are obtained. Besides, the residual error analysis for our method is presented and illustrative examples are given to demonstrate the validity and applicability of the method.
Missing value problem is common when analysing quantitative data. With the rapid growth of computing capabilities, advanced methods in particular those based on maximum likelihood estimation has been suggested to best handle the missing values problem. In this paper, two modern imputing approaches namely expectation-maximization (EM) and expectation-maximization with bootstrapping (EMB) are proposed in this paper for two kinds of linear functional relationship (LFRM) models, namely LFRM1 for full model and LFRM2 for linear functional relationship model when slope parameter is estimated using a nonparametric approach. The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. The results of the simulation study suggested that both EM and EMB methods are applicable to the LFRM with EMB algorithm outperforms the standard EM algorithm. Illustration using a practical example and a real data set is provided.
Hosoya and Merrifield-Simmons index were the two valuable topological indices in chemical graph theory. The Hosoya and Merrifield-Simmons index of the class of unicyclic graphs G(k) were investigated, according to the distance between u and v on Cm, their orderings with respect to these two topological indices were obtained.
The problem of constructing such a continuous function is called data fitting. Many times, data given only at discrete points. With interpolation, we seek a function that allows us to approximate f(x) such that functional values between the original data set values may be determined. The process of finding such a polynomial is called interpolation and one of the most important approaches used are Lagrange interpolating formula. In this study, researcher determining the polynomial interpolation by using Lagrange interpolating formula. Then, a mathematical modelling was built by using MATLAB programming to determine the polynomial interpolation for a given points using the Lagrange method. The result of the study showed that the manual calculating and the MATLAB mathematical modelling will give the same answer for evaluated x and graph.