Symmetric methods such as the implicit midpoint rule (IMR), implicit trapezoidal
rule (ITR) and 2-stage Gauss method are beneficial in solving Hamiltonian problems
since they are also symplectic. Symplectic methods have advantages over non-symplectic
methods in the long term integration of Hamiltonian problems. The study is to show
the efficiency of IMR, ITR and the 2-stage Gauss method in solving simple harmonic
oscillators (SHO). This study is done theoretically and numerically on the simple harmonic
oscillator problem. The theoretical analysis and numerical results on SHO problem
showed that the magnitude of the global error for a symmetric or symplectic method
with stepsize h is linearly dependent on time t. This gives the linear error growth when
a symmetric or symplectic method is applied to the simple harmonic oscillator problem.
Passive and active extrapolations have been implemented to improve the accuracy of the
numerical solutions. Passive extrapolation is observed to show quadratic error growth
after a very short period of time. On the other hand, active extrapolation is observed to
show linear error growth for a much longer period of time.
This paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency.
In this paper, we present a new method for solving nonlinear general two point boundary value problems. A method based on finite differences and rational function approximation and we call this method as rational approximation method. A rational approximation method is applied to construct the numerical solution for two point boundary value problems. The novel method is tested on three model problems. Thus the numerical results obtained for these model problems show the performance and efficiency of the developed method.
Similarity measurement is a critical component in any case-based reasoning (CBR) system. CBR is
a superior technique for solving new problems based on previous experiences. Main assumption in
CBR relies on the hypothesis that states similar problems should have similar solutions. This paper
describes a comparative analysis on several commonly used similarity measures (Canberra, Clark, and Normalized Euclidean distance) in retrieving phase of the case-based reasoning approach to facilitate supplier selection. In addition, the proposed agent-based supplier selection framework was designed to use customer’s defined weights to evaluate the price, volume, quality grade, and delivery date of supply materials, and also provide them with alternative products which are closest to their first order if it was out of stock. Finally, based on the proposed framework, a numerical example of the used approach is illustrated.
The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. They are well-suited for large-scale optimization problems due to their low memory requirements and least computational costs. In this paper, a new diagonal preconditioned conjugate gradient (PRECG) algorithm is designed, and this is motivated by the fact that a pre-conditioner can greatly enhance the performance of the CG method. Under mild conditions, it is shown that the algorithm is globally convergent for strongly convex functions. Numerical results are presented to show that the new diagonal PRECG method works better than the standard CG method.
Quality Function Deployment (QFD) is a structured methodology that uses customer and technical
requirements for designers and manufacturers to provide better products. Many researchers combine or
integrate the technique of QFD with other methodologies such as Theory Inventive of Problem Solving
(TRIZ) or Design for Manufacture and Assembly (DFMA) to optimise product design innovation and
improvement. The combined methodologies are even used to solve process problems. Initial literature
review of the application of stand-alone QFD poised several problems. Combining QFD with other
techniques, such as TRIZ and DFMA, has helped to address these issues and forms the basis of future
research. The integrated methods can solve main contradictory problems more precisely from product
demand analysis to product design, production and application. Review work of the literature, specifically
that on research and development of QFD, TRIZ and DFMA, showed that the said methodologies have
been widely and successfully implemented in several practical applications such as resolving conflicts
between customer and technical/engineering requirements and reducing production cost. This review work
provides an in-depth analysis of identifying and finding issues of strengths, weaknesses and outcomes
of the QFD when combined with TRIZ and also of QFD integrated with DFMA.
Required learning of the basic medical sciences based on five clinical problems was compiled by teachers and subsequently derived as 'learning needs' by students during the problem-solving process. These lists of topics were compared in terms of number of lecture-hours and when these were taught in the traditional curriculum. The findings indicate that learning from problems is not entirely free-rein and can be largely determined by teachers; topics taught earlier in the course appeared more frequently than latter topics and there was a tremendous overlap of topics in both the traditional and problem-based list. Regardless of whether lectures have been given or not, students recalled facts better if they had encountered the related clinical problem. This study also reveals that problem-based learning can be as efficient as lectures in content coverage and concludes that the lecture method be retained provided the topics are selective and are derived and sequenced appropriately with clinical problems. Problem-solving should be adopted as a teaching strategy.
Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.
Clostridium perfringens strain JJC is an effective biohydrogen and biochemical producer that was isolated from landfill leachate sludge. Here, we present the assembly and annotation of its genome, which may provide further insights into the gene interactions involved in efficient biohydrogen production.
Electroencephalogram (EEG) signal analysis is indispensable in epilepsy diagnosis as it offers valuable insights for locating the abnormal distortions in the brain wave. However, visual interpretation of the massive amounts of EEG signals is time-consuming, and there is often inconsistent judgment between experts.
The main aim of the study was to determine the effect of psychoeducation program on insight of patients with schizophrenia and to determine other factors associated with the change of the insight. This was an interventional study of 70 patients with schizophrenia who underwent a psychoeducation program. Diagnosis was confirmed using Mini International Neuropsychiatric Interview (M.I.N.I). Insight was assessed using the Schedule for the Assessment of Insight (SAI) before and after the psychoeducation programme. Effect on insight was measured as the change in SAI scores. There was an improvement in insight after the psychoeducation programme which was significant (p< 0.001). Patient’s age, shorter duration of illness and no previous history of admission to mental institution were significantly related to the improvement of insight (p< 0.05). Conclusion: Psychoeducation is an important tool in improving insight into illness among patients with schizophrenia. It needs to be given as early as possible during the course of the illness.
The preformation factor of alpha-decay process in compound nuclei is microscopically proposed with a new perspective. The formation of alpha particle inside the parent nuclei is considered as a quantum-mechanical state which is yielded from a certain interaction among the valance nucleons. This interaction is very similar to that one responsible for the formation of the quasi-bound states in many-body system. This introduced microscopic perspective might give more insight to the understanding of the nuclear structure in the compound nuclei.
Assembly line balancing is well-known in mass production system but this problem is non-deterministicpolynomial-time(NP)-hard, even for a simple straight line. Although several heuristic methods havebeen introduced and used by researchers, knowing and using an effective method in solving these typesof problems in less computational time have a considerable place in the area of line balancing problem.In this research, a new heuristic approach, known as critical node method (CNM), was introduced andtested by solving several test problems available in the literature so as to solve straight assembly lines.Finally, the obtained results are compared with 9 other heuristic rules in some performance measures.Thus, it is concluded that the proposed CNM is better than the rest in all the measures.
The steady two dimensional magnetohydrodynamic (MHD) boundary layer flow and heat transfer over a stretching/shrinking permeable wedge is numerically investigated. The partial differential equations governing the flow and heat transfer are transformed into a system of ordinary differential equations using a similarity transformation. These equations are then solved numerically using the boundary value problem solver, bvp4c in Matlab software. It is found that dual solutions exist for a certain range of the shrinking strength. A stability analysis is performed to identify which solution is stable and physically reliable.
Carbon nanotube reinforced aluminium matrix composites (Al-CNTs) have been widely used in aerospace and automotive industries where high quality and strength is required. The enhanced mechanical properties of Al-CNTs are closely related to processing technique due to challenges within production of these composite materials. In the current review, solid state processing techniques used for synthesizing Al-CNTs have been reviewed to provide an insight into the features and capabilities of each technique regarding the incorporation of CNT reinforcements. To conclude, the mechanical performance of Al-CNT composites is mainly decided by the capability of each technique in the dispersion of CNTs within the aluminum matrix.
We study the photoelectron spectra by intense laser pulses with arbitrary time dependence and phase within the Keldysh framework. An efficient semianalytical approach using analytical transition matrix elements for hydrogenic atoms in any initial state enables efficient and accurate computation of the photoionization probability at any observation point without saddle point approximation, providing comprehensive three dimensional photoelectron angular distribution for linear and elliptical polarizations, that reveal the intricate features and provide insights on the photoionization characteristics such as angular dispersions, shift and splitting of photoelectron peaks from the tunneling or above threshold ionization(ATI) regime to non-adiabatic(intermediate) and multiphoton ionization(MPI) regimes. This facilitates the study of the effects of various laser pulse parameters on the photoelectron spectra and their angular distributions. The photoelectron peaks occur at multiples of 2ħω for linear polarization while odd-ordered peaks are suppressed in the direction perpendicular to the electric field. Short pulses create splitting and angular dispersion where the peaks are strongly correlated to the angles. For MPI and elliptical polarization with shorter pulses the peaks split into doublets and the first peak vanishes. The carrier envelope phase(CEP) significantly affects the ATI spectra while the Stark effect shifts the spectra of intermediate regime to higher energies due to interference.
A prescriptive model approach in decision making could help achieve better diagnostic accuracy in clinical practice through methods that are less reliant on probabilistic assessments. Various prescriptive measures aimed at regulating factors that influence heuristics and clinical reasoning could support clinical decision-making process. Clinicians could avoid time-consuming decision-making methods that require probabilistic calculations. Intuitively, they could rely on heuristics to obtain an accurate diagnosis in a given clinical setting. An extensive literature review of cognitive psychology and medical decision-making theory was performed to illustrate how heuristics could be effectively utilized in daily practice. Since physicians often rely on heuristics in realistic situations, probabilistic estimation might not be a useful tool in everyday clinical practice. Improvements in the descriptive model of decision making (heuristics) may allow for greater diagnostic accuracy.
In this paper, two approaches were introduced to obtain Stackelberg solutions for two-level linear fractional programming problems with interval coefficients in the objective functions. The approaches were based on the Kth best method and the method for solving linear fractional programming problems with interval coefficients in the objective function. In the first approach, linear fractional programming with interval coefficients in the objective function and linear programming were utilized to obtain Stackelberg solution, but in the second approach only linear programming is used. Since a linear fractional programming with interval coefficients can be equivalently transformed into a linear programming, therefore both of approaches have same results. Numerical examples demonstrate the feasibility and effectiveness of the methods.
In this present study, microalgal phycobiliproteins were isolated and purified via potential biphasic processing technique for pharmaceutical as well as food applications. The algal pre-treatment techniques were studied to enhance the yield of microalgal phycobiliproteins from the biomass. The proposed methods were optimised to obtain the best recovery yield of phycobiliproteins that can be isolated from the biomass. The phycobiliproteins were further purified using liquid biphasic system. The results showed that microalgal phycobiliproteins of high purity and yield was achieved using sonication treatment (20% power, 50% duty cycle and 7 min of irradiation time) with the biphasic system, where the purification fold of 6.17 and recovery yield of 94.89% was achieved. This work will provide insights towards the effective downstream processing of biomolecules from microalgae.