Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants.     

Graph rigidity, cyclic belief propagation, and point pattern matching

A recent paper \cite{CaeCaeSchBar06} proposed a provably optimal, polynomial time method for performing near-isometric point pattern matching by means of exact probabilistic inference in a chordal graphical model. Its fundamental result is that the chordal graph in question is shown to be \emph{globally rigid}, implying that exact inference provides the \emph{same} matching solution as exact inference in a complete graphical model. This implies that the algorithm is optimal when there is no noise in the point patterns. In this paper, we present a new graph which is also globally rigid but has an advantage over the graph proposed in \cite{CaeCaeSchBar06}: its maximal clique size is smaller, rendering inference significantly more efficient. However, this graph is not chordal and thus standard Junction Tree algorithms cannot be directly applied. Nevertheless, we show that loopy belief propagation in such a graph converges to the optimal solution. This allows us to retain the optimality guarantee in the noiseless case, while substantially reducing both memory requirements and processing time. Our experimental results show that the accuracy of the proposed solution is indistinguishable from that of \cite{CaeCaeSchBar06} when there is noise in the point patterns.     

Distributed Latency-Energy Minimization and interference avoidance in TDMA Wireless Sensor Networks

This paper presents Latency-Energy Minimization Medium Access (LEMMA), a new TDMA-based MAC protocol for Wireless Sensor Networks (WSNs), specially suited to extend the lifetime of networks supporting alarm-driven, delay-sensitive applications characterized by convergecast traffic patterns and sporadic traffic generation. Its cascading time-slot assignment scheme conciliates low end-to-end latency with a low duty-cycle, while supporting multi-sink WSN topologies. Unlike most of the current solutions, LEMMA’s time-slot allocation protocol makes decisions based on the interference actually experienced by the nodes, instead of following the simple but potentially ineffective n-hop approach. Simulation results are presented to demonstrate the ineffectiveness of the n-hop time-slot allocation in comparison with LEMMA, as well as to evaluate the performance of LEMMA against L-MAC, T-MAC and Low Power Listening. The results show that under the target scenario conditions, LEMMA presents lower interference between assigned time-slots and lower end-to-end latency, while matching its best contender in terms of energy-efficiency.     

Clinical and epidemiological findings during a measles outbreak occurring in a population with a high vaccination coverage

Malignant mesothelioma is caused almost exclusively by occupational exposure to asbestos. During the past few years, however, increasing evidence has mounted that background exposure to asbestos could be sufficient to cause mesothelioma. Treatment of malignant mesothelioma remains a big problem. Some new approaches are on their way, and the most exciting ones are local immunotherapy in very early cases. Some success has been reported with local interferon treatment. As for treatment of metastatic pleural disease, the main purpose is symptomatic relief of dyspnea caused by fluid accumulation. The best way to achieve a lasting palliation is pleurodesis, and the most common way to do this, is by chemical means. The drug of choice in the United States has for many years been tetracycline, but since injectable tetracycline is no longer available, some substitute must be found. The substance that will "win" is not yet clear, but the two leading contestants are talc and doxycycline. Bleomycin also has its supporters, and a dark horse is quinacrine, which although not easily available in the United States, has been used in many European centers for decades.     

A computational model for developing semantic web-based educational systems

Recently, some initiatives to start the so-called semantic web-based educational systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.     

Condition-based diagnosis of mechatronic systems using a fractional calculus approach

While fractional calculus (FC) is as old as integer calculus, its application has been mainly restricted to mathematics. However, many real systems are better described using FC equations than with integer models. FC is a suitable tool for describing systems characterised by their fractal nature, long-term memory and chaotic behaviour. It is a promising methodology for failure analysis and modelling, since the behaviour of a failing system depends on factors that increase the model’s complexity. This paper explores the proficiency of FC in modelling complex behaviour by tuning only a few parameters. This work proposes a novel two-step strategy for diagnosis, first modelling common failure conditions and, second, by comparing these models with real machine signals and using the difference to feed a computational classifier. Our proposal is validated using an electrical motor coupled with a mechanical gear reducer.     

Distributed planning and control systems for the virtual enterprise: organizational requirements and development life-cycle

This paper describes the requirements analysis and system specification of an Order Promise module to be used as part of a broader Decision Support System for production and operations planning of a Virtual Enterprise. This work is part of a broader project with a particular focus on the microelectronics industry which is a good example of Virtual Enterprise, and where a quick response to the customers needs and to unpredictable changes in production conditions is considered a major factor for success. First, the analysis and specification are presented within a development framework that involves the study of organizational issues of semiconductor enterprises. The use of ontological engineering for supporting the communication and shared understanding of the system concepts is explained and a virtual enterprise ontology is outlined. Following the clarification of the concept of virtual enterprise, the generic techno-organizational requirements for the information system are derived. Finally, a specification of the global planning module and a more detailed one regarding the order promise module is presented.     

A modular Petri net to modeling and scenario analysis of a network of road traffic signals

The dynamic behavior of a group of traffic signals controlling a network of intersections is a complex discrete event system that can be modeled by Petri nets. The approach used in this paper proposes a components-based design, which increases modularity, reduces complexity and is a good practice according to modern Systems Engineering. The main system elements are specified based on the proposed Petri net component with time intervals associated to places. The specified models are simulated through the common token player algorithm, and formal analysis using invariants and theorem proving are applied to verify models' soundness and to reason on specific scenarios.     

He scattering on a TiO2(1 1 0) surface

We present measurements of energy-losses and neutralisation of helium ions on a TiO₂(1 1 0) surface at low keV energies. Measurements were performed in the 1–4 keV energy range. The target azimuthal orientation dependence of total scattering intensity profiles, energy-losses and probability of electron capture or loss were determined. On the basis of Marlowe simulations it is concluded that ion scattering intensities give indications about defects regarding surface bridging O atoms. Variations in energy losses for different scattering directions are reported. Ion fraction measurements were made using both incident ions and neutrals. Similar ion fractions were found indicating that He is efficiently neutralised and ions result from reionisation. These ion fractions are found to depend on the azimuthal orientation and have a minimum along the main crystallographic directions.