Reciprocal Tree-Like Fractal Structures

Sometimes the complex structures of nature inspire human constructions. Gothic construction has shown that forces can cross space along intricate paths that may even be arbitrary if correctly dimensioned. In some way, ribbed structures are like trees where the branches conduct forces instead of sap; they operate as branches and trunks descending by fractal ways. Here we discuss reciprocal tree-like fractal structures and the difficulty in their design and erection and solutions for constructive details, as well as the possible analytical questions and automatic generation by means of proper software. The results are shown in the design of the Natural Interpretation Centre in Melilla where we have proposed two connected trees like shown at figures included below.     

Gaussian,Lobatto and Radau positive quadrature rules with a prescribed abscissa

For a given $\theta \in (a,b)$ , we investigate the question whether there exists a positive quadrature formula with maximal degree of precision which has the prescribed abscissa $\theta $ plus possibly $a$ and/or $b$ , the endpoints of the interval of integration. This study relies on recent results on the location of roots of quasi-orthogonal polynomials. The above positive quadrature formulae are useful in studying problems in one-sided polynomial $L_1$ approximation.     

Technische Möglichkeiten und Akzeptanz mobiler Anwendungen

Mobile data communication applications, referred to in this paper as mobile applications, were one of the technological innovation and investment targets in recent years. From the past it became obvious that mono-disciplinary approaches to investigate mobile applications have shortcomings when it comes to successful innovation and investment decisions as interdependencies are insufficiently addressed. The paper therefore aims at structuring the scientific contributions of computer science, business economics and sociology in the context of mobile applications to approximate a holistic understanding comprising technological feasibility, economic opportunities and human needs.     

New possibilistic method for discovering linear local behavior using hyper-Gaussian distributed membership function

This paper presents a method to find a model of a system based on the integration of a set of local models. Mainly, properties are sought for the local models: independence of clusters and interpretability of their validity. This has been achieved through the introduction of a possibilistic clustering for the first property and a pre-fixed shape of the membership functions for the second one. A new cost index for the clustering optimization problem has been defined consisting of two terms: one for global error and another for local errors. By giving higher importance to the local errors term, local models valid regionally can be found. To avoid local optima and numerical issues, the parameters of the models are found using global optimization. This new method has been applied to several data sets, and results show how the desired characteristics can be achieved in the resulting models.     

Recognition of circular patterns on GPUs: Performance analysis and contributions

We develop a novel approach for computing the circle Hough transform entirely on graphics hardware (GPU). A primary role is assigned to vertex processors and the rasterizer, overshadowing the traditional foreground of pixel processors and enhancing parallel processing. Resources like the vertex cache or blending units are studied too, with our set of optimizations leading to extraordinary peak gain factors exceeding 358x over a typical CPU execution. Software optimizations, like the use of precomputed tables or gradient information and hardware improvements, like hyperthreading and multicores are explored on CPUs as well. Overall, the GPU exhibits better scalability and much greater parallel performance to become a solid alternative for computing the classical circle Hough transform versus those optimal methods run on emerging multicore architectures.     

Energy optimization for CAN bus and media controls in electric vehicles using deep learning algorithms

The Journal of Supercomputing - This study offers a neural network-based deep learning method for energy optimization modeling in electric vehicles (EV). The pre-processed driving cycle is...     

Identifying routes and organizational practices for resilient performance: a study in the construction industry

Cognition, Technology & Work - Modern organizations live in a context of political, economic, technological, social and environmental changes for which they need to be prepared to adapt and...     

Correction to: Uniform and scalable sampling of highly configurable systems

Empirical Software Engineering - Testing Internet of Things (IoT) systems is challenging. This is not only because of the various aspects of IoT systems, such as software, hardware, and network...     

A quantitative approach to ranking corporate law precedents in the Brazilian Superior Court of Justice

This paper aims to contribute to the goal of finding influential legal precedents by quantitative methods. A lot of work has been made in this direction worldwide, especially in the context of common law jurisdictions. However, this type of work is extremely scarce in the Brazilian literature. In addition, our work also contributes to the research of network analysis and the law by applying these methods to unprecedented amount of data and narrowing our inquiry to a single law area, corporate law. Furthermore, whereas most of the literature applying network analysis to judicial decisions had access to readily available data on the citations to precedent within each ruling, our raw data was nothing but the full text of decisions. We focus on data produced by the Superior Court of Justice (STJ), the highest court in Brazil for matters of federal law, including statutory interpretation of civil, criminal and corporate law. The Court issued an astonishing 282040 opinions tagged as related to corporate law between 2008 and 2018. This amount of cases is unparalleled internationally for superior courts and for studies in network analysis and law. In our results, we rank precedents quantitatively based on the citations they receive and make. We also qualitatively analyze some of the results, especially related to groups identified in the network with the Modularity algorithm. Our findings also reveal that corporate law jurisprudence in the STJ is quantitatively dominated by a few legal issues around one single theme that is only tangentially related to corporate law. That is, a type of contract used for the expansion of telephone landlines, which also allowed the consumer to become a shareholder of the telecommunication company. This comparison is especially pertinent because the utter lack of data on the quantitative weight of STJ precedents means the national literature has been operating in a void of objective measurements, one which has been filled with cherry-picked rulings and subjective ranking criteria.