A Fast Splitting Method for efficient Split Bregman Iterations

In this paper we propose a new fast splitting algorithm to solve the Weighted Split Bregman minimization problem in the backward step of an accelerated Forward-Backward algorithm. Beside proving the convergence of the method, numerical tests, carried out on different imaging applications, prove the accuracy and computational efficiency of the proposed algorithm

Teaching Model Views with UML and OCL

The specification of any non-trivial system is normally composed of a set of models. Each model describes a different view of the system, focuses on a particular set of concerns, and uses its own notation. For example, UML defines a set of diagrams for modelling the structure and behavior of any software system. One of the problems we perceived with our students is that they are able to understand each one of these diagrams, but they have problems understanding how they are related, and how the overall system specifications work when composed of a set of views. This paper presents a simple case study that we have developed and successfully used in class, which permits students developing the principal views of a system, simulate them, and check their relations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

FAKTOR-FAKTOR YANG MEMPENGARUHI KUALITAS PELAPORAN KEUANGAN DAERAH (STUDI PADA SATUAN KERJA PERANGKAT KABUPATEN ACEH TENGAH)

ABSTRAKPenelitian ini bertujuan untuk menguji pengaruh kualitas aparatur daerah, pemanfaatan teknologi informasi, dan pengawasan keuangan daerah baik secara bersama-sama maupun secara terpisah terhadap kualitas pelaporan keuangan daerah pada Satuan Kerja Perangkat Daerah di Kabupaten Aceh Tengah. Populasi dalam penelitian ini adalah seluruh institusi/lembaga yang meliputi kantor, dinas dan badan pada Kabupaten Aceh Tengah. Sebanyak 28 SKPK (Satuan Kerja Perangkat Kabupaten) dan untuk masing-masing SKPKterdiri dari 3 orang yang terdiri dari kepala SKPK atau Pengguna Anggaran, kepala bagian akuntansi dan staf bagian akuntansi sebagai responden penelitian. Sumber data dalam penelitian ini menggunakan data primer yaitu hasil perolehan kuesioner dari responden penelitian. Sedangkan teknik pengumpulan data penelitian dilakukan dengan teknik penyebaran kuesioner. Metode analisis yang digunakan yaitu Analisis Regresi Linear Berganda. Hasil penelitian menunjukkan bahwa kualitas aparatur daerah, pemanfaatan teknologi informasi, dan pengawasan keuangan daerah baik secara bersama-sama maupun secara terpisah berpengaruh terhadap kualitas pelaporan keuangan daerah pada Satuan Kerja Perangkat Daerah di Kabupaten Aceh Tengah.Kata kunci: Kualitas Aparatur Daerah, Pemanfaatan Teknologi Informasi, Pengawasan Keuangan Daerah, Kualitas Pelaporan Keuangan Daerah

Concurrent Model Transformations with Linda

Nowadays, model transformations languages and engines use a sequential execution model. This is, only one execution thread deals with the whole transformation. However, model transformations dealing with very large models, such as those used in biology or aerospace applications, require concurrent solutions in order to speed up their performance. In this ongoing work we explore the use of Linda for implementing a set of basic mechanisms to enable concurrent model transformations, and present our initial results.Proyectos TIN2011-23795, TIN2011-15497-E y Andalucía Tech Campus de Excelencia

A Linda-based Platform for the Parallel Execution of Out-place Model Transformations

Context: The performance and scalability of model transformations is gaining interest as industry is progressively adopting model-driven techniques and multicore computers are becoming commonplace. However, existing model transformation engines are mostly based on sequential and in-memory execution strategies, and thus their capabilities to transform large models in parallel and distributed environments are limited. Objective: This paper presents a solution that provides concurrency and distribution to model transformations. Method: Inspired by the concepts and principles of the Linda coordination language, and the use of data parallelism to achieve parallelization, a novel Javabased execution platform is introduced. It offers a set of core features for the parallel execution of out-place transformations that can be used as a target for high-level transformation language compilers. Results: Significant gains in performance and scalability of this platform are reported with regard to existing model transformation solutions. These results are demonstrated by running a model transformation test suite, and by its comparison against several state-of-the-art model transformation engines. Conclusion: Our Linda-based approach to the concurrent execution of model transformations can serve as a platform for their scalable and efficient implementation in parallel and distributed environments.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Employing Classifying Terms for Testing Model Transformations

This contribution proposes a new technique for developing test cases for UML and OCL models. The technique is based on an approach that automatically constructs object models for class models enriched by OCL constraints. By guiding the construction process through so-called classifying terms, the built test cases in form of object models are classified into equivalence classes. A classifying term can be an arbitrary OCL term on the class model that calculates for an object model a characteristic value. From each equivalence class of object models with identical characteristic values one representative is chosen. The constructed test cases behave significantly different with regard to the selected classifying term. By building few diverse object models, properties of the UML and OCL model can be explored effectively. The technique is applied for automatically constructing relevant source model test cases for model transformations between a source and target metamodel.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Generating Effective Test Suites for Model Transformations Using Classifying Terms

Generating sample models for testing a model transformation is no easy task. This paper explores the use of classifying terms and stratified sampling for developing richer test cases for model transformations. Classifying terms are used to define the equivalence classes that characterize the relevant subgroups for the test cases. From each equivalence class of object models, several representative models are chosen depending on the required sample size. We compare our results with test suites developed using random sampling, and conclude that by using an ordered and stratified approach the coverage and effectiveness of the test suite can be significantly improved.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Photon-assisted shot noise in graphene in the Terahertz range

When subjected to electromagnetic radiation, the fluctuation of the electronic current across a quantum conductor increases. This additional noise, called photon-assisted shot noise, arises from the generation and subsequent partition of electron-hole pairs in the conductor. The physics of photon-assisted shot noise has been thoroughly investigated at microwave frequencies up to 20 GHz, and its robustness suggests that it could be extended to the Terahertz (THz) range. Here, we present measurements of the quantum shot noise generated in a graphene nanoribbon subjected to a THz radiation. Our results show signatures of photon-assisted shot noise, further demonstrating that hallmark time-dependant quantum transport phenomena can be transposed to the THz range.Comment: includes supplemental materia

Towards Distributed Model Transformations with LinTra

Performance and scalability of model transformations are becoming prominent topics in Model-Driven Engineering. In previous works we introduced LinTra, a platform for executing model transformations in parallel. LinTra is based on the Linda model of a coordination language and is intended to be used as a middleware where high-level model transformation languages are compiled. In this paper we present the initial results of our analyses on the scalability of out-place model-to-model transformation executions in LinTra when the models and the processing elements are distributed over a set of machines.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Recurrent Neural Networks Applied to GNSS Time Series for Denoising and Prediction

Global Navigation Satellite Systems (GNSS) are systems that continuously acquire data and provide position time series. Many monitoring applications are based on GNSS data and their efficiency depends on the capability in the time series analysis to characterize the signal content and/or to predict incoming coordinates. In this work we propose a suitable Network Architecture, based on Long Short Term Memory Recurrent Neural Networks, to solve two main tasks in GNSS time series analysis: denoising and prediction. We carry out an analysis on a synthetic time series, then we inspect two real different case studies and evaluate the results. We develop a non-deep network that removes almost the 50% of scattering from real GNSS time series and achieves a coordinate prediction with 1.1 millimeters of Mean Squared Error