Maude Object-Oriented Action Tool

MAIDL, André Murbach; CARVILHE, Claudio; MUSICANTE, Martin A. Maude Object-Oriented Action Tool. Electronic Notes in Theoretical Computer Science. [S.l:s.n], 2008.

Transactions and schema evolution in a persistent object-oriented programming system

Applications are subject of a continuous evolution process with a profound impact on their underlining data model, hence requiring frequent updates in the applications' class structure and database structure as well. This twofold problem, schema evolution and instance adaptation, usually known as database evolution, is addressed in this thesis. Additionally, we address concurrency and error recovery problems with a novel meta-model and its aspect-oriented implementation. Modern object-oriented databases provide features that help programmers deal with object persistence, as well as all related problems such as database evolution, concurrency and error handling. In most systems there are transparent mechanisms to address these problems, nonetheless the database evolution problem still requires some human intervention, which consumes much of programmers' and database administrators' work effort. Earlier research works have demonstrated that aspect-oriented programming (AOP) techniques enable the development of flexible and pluggable systems. In these earlier works, the schema evolution and the instance adaptation problems were addressed as database management concerns. However, none of this research was focused on orthogonal persistent systems. We argue that AOP techniques are well suited to address these problems in orthogonal persistent systems. Regarding the concurrency and error recovery, earlier research showed that only syntactic obliviousness between the base program and aspects is possible. Our meta-model and framework follow an aspect-oriented approach focused on the object-oriented orthogonal persistent context. The proposed meta-model is characterized by its simplicity in order to achieve efficient and transparent database evolution mechanisms. Our meta-model supports multiple versions of a class structure by applying a class versioning strategy. Thus, enabling bidirectional application compatibility among versions of each class structure. That is to say, the database structure can be updated because earlier applications continue to work, as well as later applications that have only known the updated class structure. The specific characteristics of orthogonal persistent systems, as well as a metadata enrichment strategy within the application's source code, complete the inception of the meta-model and have motivated our research work. To test the feasibility of the approach, a prototype was developed. Our prototype is a framework that mediates the interaction between applications and the database, providing them with orthogonal persistence mechanisms. These mechanisms are introduced into applications as an {\it aspect} in the aspect-oriented sense. Objects do not require the extension of any super class, the implementation of an interface nor contain a particular annotation. Parametric type classes are also correctly handled by our framework. However, classes that belong to the programming environment must not be handled as versionable due to restrictions imposed by the Java Virtual Machine. Regarding concurrency support, the framework provides the applications with a multithreaded environment which supports database transactions and error recovery. The framework keeps applications oblivious to the database evolution problem, as well as persistence. Programmers can update the applications' class structure because the framework will produce a new version for it at the database metadata layer. Using our XML based pointcut/advice constructs, the framework's instance adaptation mechanism is extended, hence keeping the framework also oblivious to this problem. The potential developing gains provided by the prototype were benchmarked. In our case study, the results confirm that mechanisms' transparency has positive repercussions on the programmer's productivity, simplifying the entire evolution process at application and database levels. The meta-model itself also was benchmarked in terms of complexity and agility. Compared with other meta-models, it requires less meta-object modifications in each schema evolution step. Other types of tests were carried out in order to validate prototype and meta-model robustness. In order to perform these tests, we used an OO7 small size database due to its data model complexity. Since the developed prototype offers some features that were not observed in other known systems, performance benchmarks were not possible. However, the developed benchmark is now available to perform future performance comparisons with equivalent systems. In order to test our approach in a real world scenario, we developed a proof-of-concept application. This application was developed without any persistence mechanisms. Using our framework and minor changes applied to the application's source code, we added these mechanisms. Furthermore, we tested the application in a schema evolution scenario. This real world experience using our framework showed that applications remains oblivious to persistence and database evolution. In this case study, our framework proved to be a useful tool for programmers and database administrators. Performance issues and the single Java Virtual Machine concurrent model are the major limitations found in the framework.

Object-Oriented Modeling Simulation and Control of Activated Sludge Process

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Programming Assignment of Programming 3: an Object-Oriented Version of Conway’s Game of Life

These are the instructions for a programming assignment of the subject Programming 3 taught at University of Alicante in Spain. The objective of the assignment is to build an object-oriented version of Conway's game of life in Java. The assignment is divided into four sub-assignments.

Adaptive Software Fault Prediction Approach Using Object-Oriented Metrics

As users continually request additional functionality, software systems will continue to grow in their complexity, as well as in their susceptibility to failures. Particularly for sensitive systems requiring higher levels of reliability, faulty system modules may increase development and maintenance cost. Hence, identifying them early would support the development of reliable systems through improved scheduling and quality control. Research effort to predict software modules likely to contain faults, as a consequence, has been substantial. Although a wide range of fault prediction models have been proposed, we remain far from having reliable tools that can be widely applied to real industrial systems. For projects with known fault histories, numerous research studies show that statistical models can provide reasonable estimates at predicting faulty modules using software metrics. However, as context-specific metrics differ from project to project, the task of predicting across projects is difficult to achieve. Prediction models obtained from one project experience are ineffective in their ability to predict fault-prone modules when applied to other projects. Hence, taking full benefit of the existing work in software development community has been substantially limited. As a step towards solving this problem, in this dissertation we propose a fault prediction approach that exploits existing prediction models, adapting them to improve their ability to predict faulty system modules across different software projects.

Code pattern analysis of object-oriented programming languages

Code patterns, including programming patterns and design patterns, are good references for programming language feature improvement and software re-engineering. However, to our knowledge, no existing research has attempted to detect code patterns based on code clone detection technology. In this study, we build upon the previous work and propose to detect and analyze code patterns from a collection of open source projects using NiPAT technology. Because design patterns are most closely associated with object-oriented languages, we choose Java and Python projects to conduct our study. The tool we use for detecting patterns is NiPAT, a pattern detecting tool originally developed for the TXL programming language based on the NiCad clone detector. We extend NiPAT for the Java and Python programming languages. Then, we try to identify all the patterns from the pattern report and classify them into several different categories. In the end of the study, we analyze all the patterns and compare the differences between Java and Python patterns.

Apports de la texture multibande dans la classification orientée-objets d'images multisources (optique et radar).

Résumé : La texture dispose d’un bon potentiel discriminant qui complète celui des paramètres radiométriques dans le processus de classification d’image. L’indice Compact Texture Unit (CTU) multibande, récemment mis au point par Safia et He (2014), permet d’extraire la texture sur plusieurs bandes à la fois, donc de tirer parti d’un surcroît d’informations ignorées jusqu’ici dans les analyses texturales traditionnelles : l’interdépendance entre les bandes. Toutefois, ce nouvel outil n’a pas encore été testé sur des images multisources, usage qui peut se révéler d’un grand intérêt quand on considère par exemple toute la richesse texturale que le radar peut apporter en supplément à l’optique, par combinaison de données. Cette étude permet donc de compléter la validation initiée par Safia (2014) en appliquant le CTU sur un couple d’images optique-radar. L’analyse texturale de ce jeu de données a permis de générer une image en « texture couleur ». Ces bandes texturales créées sont à nouveau combinées avec les bandes initiales de l’optique, avant d’être intégrées dans un processus de classification de l’occupation du sol sous eCognition. Le même procédé de classification (mais sans CTU) est appliqué respectivement sur : la donnée Optique, puis le Radar, et enfin la combinaison Optique-Radar. Par ailleurs le CTU généré sur l’Optique uniquement (monosource) est comparé à celui dérivant du couple Optique-Radar (multisources). L’analyse du pouvoir séparateur de ces différentes bandes à partir d’histogrammes, ainsi que l’outil matrice de confusion, permet de confronter la performance de ces différents cas de figure et paramètres utilisés. Ces éléments de comparaison présentent le CTU, et notamment le CTU multisources, comme le critère le plus discriminant ; sa présence rajoute de la variabilité dans l’image permettant ainsi une segmentation plus nette, une classification à la fois plus détaillée et plus performante. En effet, la précision passe de 0.5 avec l’image Optique à 0.74 pour l’image CTU, alors que la confusion diminue en passant de 0.30 (dans l’Optique) à 0.02 (dans le CTU).

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.

Identificação de áreas sob maior risco para leishmaniose visceral na cidade de Teresina, Piauí, Brasil

O propósito desta Tese foi detectar e caracterizar áreas sob alto risco para leishmaniose visceral (LV) e descrever os padrões de ocorrência e difusão da doença, entre os anos de 1993 a 1996 e 2001 a 2006, em Teresina, Piauí, por meio de métodos estatísticos para análise de dados espaciais, sistemas de informações geográficas e imagens de sensoriamento remoto. Os resultados deste estudo são apresentados na forma de três manuscritos. O primeiro usou análise de dados espaciais para identificar as áreas com maior risco de LV na área urbana de Teresina entre 2001 e 2006. Os resultados utilizando razão de kernels demonstraram que as regiões periféricas da cidade foram mais fortemente afetadas ao longo do período analisado. A análise com indicadores locais de autocorrelação espacial mostrou que, no início do período de estudo, os agregados de alta incidência de LV localizavam-se principalmente na região sul e nordeste da cidade, mas nos anos seguintes os eles apareceram também na região norte da cidade, sugerindo que o padrão de ocorrência de LV não é estático e a doença pode se espalhar ocasionalmente para outras áreas do município. O segundo estudo teve como objetivo caracterizar e predizer territórios de alto risco para ocorrência da LV em Teresina, com base em indicadores socioeconômicos e dados ambientais, obtidos por sensoriamento remoto. Os resultados da classificação orientada a objeto apontam a expansão da área urbana para a periferia da cidade, onde antes havia maior cobertura de vegetação. O modelo desenvolvido foi capaz de discriminar 15 conjuntos de setores censitário (SC) com diferentes probabilidades de conterem SC com alto risco de ocorrência de LV. O subconjunto com maior probabilidade de conter SC com alto risco de LV (92%) englobou SC com percentual de chefes de família alfabetizados menor que a mediana (≤64,2%), com maior área coberta por vegetação densa, com percentual de até 3 moradores por domicílio acima do terceiro quartil (>31,6%). O modelo apresentou, respectivamente, na amostra de treinamento e validação, sensibilidade de 79% e 54%, especificidade de 74% e 71%, acurácia global de 75% e 67% e área sob a curva ROC de 83% e 66%. O terceiro manuscrito teve como objetivo avaliar a aplicabilidade da estratégia de classificação orientada a objeto na busca de possíveis indicadores de cobertura do solo relacionados com a ocorrência da LV em meio urbano. Os índices de acurácia foram altos em ambas as imagens (>90%). Na correlação da incidência da LV com os indicadores ambientais verificou-se correlações positivas com os indicadores Vegetação densa, Vegetação rasteira e Solo exposto e negativa com os indicadores Água, Urbana densa e Urbana verde, todos estatisticamente significantes. Os resultados desta tese revelam que a ocorrência da LV na periferia de Teresina está intensamente relacionada às condições socioeconômicas inadequadas e transformações ambientais decorrentes do processo de expansão urbana, favorecendo a ocorrência do vetor (Lutzomyia longipalpis) nestas regiões.

Umbrella pine above ground biomass estimation with very high spatial resolution satellite images

Above ground biomass is frequently estimated with forest inventory data and an extrapolation method for the per unit area evaluations. This procedure is labour demanding and costly. In this study above ground biomass functions, whose independent variable is crown horizontal projection, were developed. Multi-resolution segmentation method and object-oriented classification, based on very high spatial resolution satellite images, were used to obtain the area of tree crown horizontal projection for umbrella pine (Pinus pinea L.). A set of inventory plots were measured and with existing allometric functions for this species above ground biomass per tree and per plot were calculated. The two data sets were used to fit linear functions both for individual plot and their cumulative values. The results show a good performance of the models. Errors smaller than 10% are obtained for stand areas greater than 1.4 ha. These functions have the advantages of estimating above ground biomass for all the area under study or surveillance, not requiring forest inventory; allow monitoring in short time periods; and are easily implemented in a geographical information system environment.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.

A classification of concurrency failures in java components

The Java programming language supports concurrency. Concurrent programs are hard to test due to their inherent non-determinism. This paper presents a classification of concurrency failures that is based on a model of Java concurrency. The model and failure classification is used to justify coverage of synchronization primitives of concurrent components. This is achieved by constructing concurrency flow graphs for each method call. A producer-consumer monitor is used to demonstrate how the approach can be used to measure coverage of concurrency primitives and thereby assist in determining test sequences for deterministic execution.

A Knowledge-Oriented Technology of System-Objective Analysis and Modelling of Business-Systems

A new original method and CASE-tool of system analysis and modelling are represented. They are for the first time consistent with the requirements of object-oriented technology of informational systems design. They essentially facilitate the construction of organisational systems models and increase the quality of the organisational designing and basic technological processes of object application developing.