Caracterização dinâmica de um edifício existente de betão armado através de ensaios de vibração ambiental

Dissertação de natureza Científica para obtenção do grau de Mestre em Engenharia Civil

Automated symbolic and numeric procedure for manipulator rigid-body dynamic significance analysis and simplification

This paper describes an automated procedure for analysing the significance of each of the many terms in the equations of motion for a serial-link robot manipulator. Significance analysis provides insight into the rigid-body dynamic effects that are significant locally or globally in the manipulator's state space. Deleting those terms that do not contribute significantly to the total joint torque can greatly reduce the computational burden for online control, and a Monte-Carlo style simulation is used to investigate the errors thus introduced. The procedures described are a hybrid of symbolic and numeric techniques, and can be readily implemented using standard computer algebra packages.

Bucket attack on numeric set watermarking model and safeguards

Numeric set watermarking is a way to provide ownership proof for numerical data. Numerical data can be considered to be primitives for multimedia types such as images and videos since they are organized forms of numeric information. Thereby, the capability to watermark numerical data directly implies the capability to watermark multimedia objects and discourage information theft on social networking sites and the Internet in general. Unfortunately, there has been very limited research done in the field of numeric set watermarking due to underlying limitations in terms of number of items in the set and LSBs in each item available for watermarking. In 2009, Gupta et al. proposed a numeric set watermarking model that embeds watermark bits in the items of the set based on a hash value of the items’ most significant bits (MSBs). If an item is chosen for watermarking, a watermark bit is embedded in the least significant bits, and the replaced bit is inserted in the fractional value to provide reversibility. The authors show their scheme to be resilient against the traditional subset addition, deletion, and modification attacks as well as secondary watermarking attacks. In this paper, we present a bucket attack on this watermarking model. The attack consists of creating buckets of items with the same MSBs and determine if the items of the bucket carry watermark bits. Experimental results show that the bucket attack is very strong and destroys the entire watermark with close to 100% success rate. We examine the inherent weaknesses in the watermarking model of Gupta et al. that leave it vulnerable to the bucket attack and propose potential safeguards that can provide resilience against this attack.

Robust numeric set watermarking : numbers don’t lie

Ever since Cox et. al published their paper, “A Secure, Robust Watermark for Multimedia” in 1996 [6], there has been tremendous progress in multimedia watermarking. The same pattern re-emerged with Agrawal and Kiernan publishing their work “Watermarking Relational Databases” in 2001 [1]. However, little attention has been given to primitive data collections with only a handful works of research known to the authors [11, 10]. This is primarily due to the absence of an attribute that differentiates marked items from unmarked item during insertion and detection process. This paper presents a distribution-independent, watermarking model that is secure against secondary-watermarking in addition to conventional attacks such as data addition, deletion and distortion. The low false positives and high capacity provide additional strength to the scheme. These claims are backed by experimental results provided in the paper.

Numeric Calculation for Transient Thermal Stress Field in Wall-Shape Metal Part During Laser Direct Forming

In order to investigate the transient thermal stress field in wall-shape metal part during laser direct forming, a FEM model basing on ANSYS is established, and its algorithm is also dealt with. Calculation results show that while the wall-shape metal part is being deposited, in X direction, the thermal stress in the top layer of the wall-shape metal part is tensile stress and in the inner of the wall-shape metal part is compressive stress. The reason causing above-mentioned thermal stress status in the wall-shape metal part is illustrated, and the influence of the time and the processing parameters on the thermal stress field in wall-shape metal part is also studied. The calculation results are consistent with experimental results in tendency.

Detecting Anomalies in Graphs with Numeric Labels

This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-related examples and validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, Yagada detects twice as many anomalies as the best-performing numeric discretization algorithm. Qualitative evaluation shows that the detected anomalies are meaningful, representing a com- bination of structural irregularities and numerical outliers.

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels

Many graph datasets are labelled with discrete and numeric attributes. Most frequent substructure discovery algorithms ignore numeric attributes; in this paper we show how they can be used to improve search performance and discrimination. Our thesis is that the most descriptive substructures are those which are normative both in terms of their structure and in terms of their numeric values. We explore the relationship between graph structure and the distribution of attribute values and propose an outlier-detection step, which is used as a constraint during substructure discovery. By pruning anomalous vertices and edges, more weight is given to the most descriptive substructures. Our method is applicable to multi-dimensional numeric attributes; we outline how it can be extended for high-dimensional data. We support our findings with experiments on transaction graphs and single large graphs from the domains of physical building security and digital forensics, measuring the effect on runtime, memory requirements and coverage of discovered patterns, relative to the unconstrained approach.

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Indoor and outdoor atmospheric fungal spores in the So Paulo metropolitan area (Brazil): species and numeric concentrations

The aim of this study was to estimate the indoor and outdoor concentrations of fungal spores in the Metropolitan Area of Sao Paulo (MASP), collected at different sites in winter/spring and summer seasons. The techniques adopted included cultivation (samples collected with impactors) and microscopic enumeration (samples collected with impingers). The overall results showed total concentrations of fungal spores as high as 36,000 per cubic meter, with a large proportion of non culturable spores (around 91% of the total). Penicillium sp. and Aspergillus sp. were the dominant species both indoors and outdoors, in all seasons tested, occurring in more than 30% of homes at very high concentrations of culturable airborne fungi [colony forming units(CFU) m(-3)]. There was no significant difference between indoor and outdoor concentrations. The total fungal spore concentration found in winter was 19% higher than that in summer. Heat and humidity were the main factors affecting fungal growth; however, a non-linear response to these factors was found. Thus, temperatures below 16A degrees C and above 25A degrees C caused a reduction in the concentration (CFU m(-3)) of airborne fungi, which fits with MASP climatalogy. The same pattern was observed for humidity, although not as clearly as with temperature given the usual high relative humidity (above 70%) in the study area. These results are relevant for public health interventions that aim to reduce respiratory morbidity among susceptible populations.

Numeric simulation of pollutant dispersion by a control-volume based on finite element method

The dispersion of pollutants in the environment is an issue of great interest as it directly affects air quality, mainly in large cities. Experimental and numerical tools have been used to predict the behavior of pollutant species dispersion in the atmosphere. A software has been developed based on the control-volume based on the finite element method in order to obtain two-dimensional simulations of Navier-Stokes equations and heat or mass transportation in regions with obstacles, varying position of the pollutant source. Numeric results of some applications were obtained and, whenever possible, compared with literature results showing satisfactory accordance. Copyright (C) 2010 John Wiley & Sons, Ltd.

Numeric evaluation of the stiffness of log-concrete composite beams submitted the cyclical load

In this paper was evaluated, using the software ANSYS, the stiffness (El) of the log-concrete composite beams, of section T, with connectors formed by bonded-in steel rods, type CA-50, disposed in X, with application of cyclical load. The stiffness of the system was evaluated through the simulation of bending tests, considered 1/2 beam, with cyclical shipment varying among 40 % and 5 % of the strength of the connection with the load relationship R=0,125, for a total of 10 load cycles applied. The numeric results show a good agreement with experimental tests.