Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function

Curve reconstruction regularly used in reverse engineering. Meanwhile, curve fitting is one of the main compositions of curve reconstruction that is usually represented by mathematical functions, most suitable for representing a set of data points, and may need to meet some constraints. Various of curve fitting studies had been done by many researchers specifically using optimisation technique. The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. Metaheuristics has strong and intelligent mechanisms to avoid being trapped in the local minimum

ANALYSING INTEGRATED PUBLIC FINANCIAL MANAGEMENT REFORMS: A CASE STUDY OF GHANA

Public sector accounting reforms have a vast potential to impact on the developing world (Hopper et al., 2016) but the explication of reform performance is only partial in the neo-classical economics framework. Accounting scholars have called for a deeper understanding of the context and conditions of accounting reforms in the less developing countries and emerging economies (LDCs/EEs) (van Helden and Uddin, 2016; Nyamori et al.,2017; Hopper et al., 2016; Goddard and Mkasiwa, 2016; Manning and McCourt, 2013; Abdul-Rahaman et al., 1997). This research sets out to understand the context of the public financial management (PFM)reforms using Ghana as an example of LDCs/EEs. The tools embedded in the institutional logics approach (ILA) are mobilised, as a meta-theoretical framework encompassing symbolic interactionism and grounded theory, to offer a constructivist-interpretivist account of the reforms. This research found that accounting changes through the PFM reforms in Ghana have been challenging to implement, and reforms outcomes have been poor to mediocre. Empirically, this study identified budget credibility as the core category in public sector accounting reforms in Ghana. The reform outcomes are reflected and constituted in the budget logics, such as over-centralization of controls, gaming, and unpredictability of flow of funds to the ministries, departments and agencies (MDAs), that have constrained the reforms. This study relates the core category to the other five main empirical categories, namely: accountability, professionalism, and financial re-engineering, automation, and policy credibility) which emerged from the study. Longitudinally, the research found that, dating back to the pre-independence era, only limited improvements have been made in the transformation of the public financial management practices to support economic development in Ghana. Opportunities to decentralize financial controls were not taken the 1980s, and the successive recent reforms have only centralized both the reforms and financial management controls. This research explains why sub-optimal accounting practices endure, the paradox of embeddedness, and constraints and possibilities of collective action to effect accounting change through reforms. The study examines the dynamics and the interplay of budget credibility and the other categorical elements within the “vampire state”, and the impact of hegemonic influences of the international community on local actors institutionalised in the polities through objectification and exteriorisation of culture. The implications of the budget credibility are explored further through the development of a substantive theory on the reforms, a processual analysis, and interinstitutional orders comprising national community logics, state logics, and international community logics that shape public sector accounting change in Ghana. This research opens up the possibility of further theoretical and empirical studies in other resource dependent countries where reforms are influenced by external donor development partners

Magyar Mesterséges Intelligencia Bibliográfia : Válogatás az 1988-96 között (esetenként korábban) megjelent publikációkból

Tartalom: referált folyóiratokban, konferencia kiadványokban, tanulmánykötetekben megjelent dolgozatok, könyvek, tankönyvek, disszertációk referenciáit, közel 190 magyar szerző/társszerző 400 (tárgyszavazott) dolgozatát tartalmazza. Függelékében az Új ALAPLAP folyóirat Jakab Ágnes által szerkesztett TUDÁSTECHNOLÓGIA c. tematikus MI-sorozat dolgozatainak jegyzéke található. Az anyagok az NJSZT által Budapesten szervezett ECAI’96 konferenciát kísérő kiállításra készültek. A Bibliográfia és a hozzá kapcsolódó Reprint Gyűjtemény az NJSZT standján volt kiállítva, míg az OMIKK adatbázisában való keresést egy oda kihelyezett terminál biztosította. A tárgyszavazást és az adatfelvitelt Kladiva Ottmár (OMIKK) irányította

Articles indexats publicats per autors de l'ETSAB

Aquest document recull els articles publicats per investigadors de l'ETSAB en revistes del Web of Science i de Scopus des de l'any 2000 fins el 2011.Preprin

Tabu search-based method for bézier curve parameterization

A very important issue in many applied fields is to construct the fitting curve that approximates a given set of data points optimally in the sense of least-squares. This problem arises in a number of areas, such as computer-aided design & manufacturing (CAD/CAM), virtual reality, medical imaging, computer graphics, computer animation, and many others. This is also a hard problem, because it is highly nonlinear, over-determined and typically involves a large number of unknown variables. A critical step in this process is to obtain a suitable parameterization of the data points. In this context, this paper introduces a new method to obtain an optimal solution for the parameterization problem of the least-squares fitting Bézier curve. Our method is based on a local search metaheuristic approach for optimization problems called tabu search. The method is applied to some simple yet illustrative examples for the cases of 2D and 3D curves. The proposed method is simple to understand, easy to implement and can be applied to any kind of smooth data points. Our experimental results show that the presented method performs very well, being able to fit the data points with a high degree of accuracy.This research has been financially supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project Ref. #TIN2012-30768, Toho University, the University of Cantabria, and the Instituto de Física de Cantabria, a mixed research center of the University of Cantabria and CSIC-Consejo Superior de Investigaciones Científicas.Peer Reviewe

Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization

Data representation is a challenging problem in areas such as font reconstruction, medical image and scanned images. Direct mathematical techniques usually give smallest errors but sometime take a much longer time to compute. Alternatively, artificial intelligence techniques are widely used for optimization problem with shorter computation time. Besides, the usage of artificial technique for data representation is getting popular lately. Thus, this thesis is dedicated for the representation of curves and surfaces. Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. These techniques have been used to optimize control points and weights in the description of spline functions used. Preprocessing components such as corner detection and chord length parameterization are also explained in this thesis. For each proposed soft computing technique, parameter tuning is done as an essential study. The sum of squares error (SSE) is used as an objective function. Therefore, this is also a minimization problem where the best values for control points and weights are found when SSE value is minimized. Rational Bézier quadratics have been utilized for the representation of curves. Reconstruction of surfaces is achieved by extending the rational Bézier quadratics to their rational Bézier bi-quadratic counterpart. Our proposed curve and surface methods with additional help from soft computing techniques have been utilized to vectorize the 2D and 3D shapes and objects

Generación informática de tipologías arquitectónicas por medio de tipologías matemáticas

Peer Reviewe

Multiple 2D self organising map network for surface reconstruction of 3D unstructured data

Surface reconstruction is a challenging task in reverse engineering because it must represent the surface which is similar to the original object based on the data obtained. The data obtained are mostly in unstructured type whereby there is not enough information and incorrect surface will be obtained. Therefore, the data should be reorganised by finding the correct topology with minimum surface error. Previous studies showed that Self Organising Map (SOM) model, the conventional surface approximation approach with Non Uniform Rational B-Splines (NURBS) surfaces, and optimisation methods such as Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimisation (PSO) methods are widely implemented in solving the surface reconstruction. However, the model, approach and optimisation methods are still suffer from the unstructured data and accuracy problems. Therefore, the aims of this research are to propose Cube SOM (CSOM) model with multiple 2D SOM network in organising the unstructured surface data, and to propose optimised surface approximation approach in generating the NURBS surfaces. GA, DE and PSO methods are implemented to minimise the surface error by adjusting the NURBS control points. In order to test and validate the proposed model and approach, four primitive objects data and one medical image data are used. As to evaluate the performance of the proposed model and approach, three performance measurements have been used: Average Quantisation Error (AQE) and Number Of Vertices (NOV) for the CSOM model while surface error for the proposed optimised surface approximation approach. The accuracy of AQE for CSOM model has been improved to 64% and 66% when compared to 2D and 3D SOM respectively. The NOV for CSOM model has been reduced from 8000 to 2168 as compared to 3D SOM. The accuracy of surface error for the optimised surface approximation approach has been improved to 7% compared to the conventional approach. The proposed CSOM model and optimised surface approximation approach have successfully reconstructed surface of all five data with better performance based on three performance measurements used in the evaluation