Guilherme Costa Carvalho Silva

Immune inspired Fault Detection and Diagnosis: A fuzzy-based approach of the negative selection algorithm and participatory clustering

This paper describes an immune-inspired system based on an alternate theory about the self-nonself distinction theory, which defines the negative selection process as a mechanism of a fuzzy system based on the affinity between antigen and T-cells. This theory may provide a decision making tool which improves the generation of detectors or even define new data monitoring in order to detect an extreme variation of the system behavior, which means anomalies occurrences. Through these algorithms, tests are performed to detect faults of a DC motor. Upon detection of faults, a participatory clustering algorithm is used to classify these faults and tested to obtain the best set of parameters to achieve the most accurate clustering for these tests in the application being discussed in the article.

A transitional view of immune inspired techniques for anomaly detection

The use of Immune Inspired approaches for anomaly detection have been adopted in the literature because of its analogy with body resistance in the human immune system provided against agents which causes diseases. There are many models in biology that attempt to explain the immune system behavior, as well some engineering systems inspired on these models. Our goal is to document the development of these models in a transitional view, some aspects which may be considered on these algorithms and on their applicability in engineering problems, with some examples.

Esthetic planning with a digital tool: A clinical report

This clinical report describes digital planning and execution using a novel software tool to enhance digital workflow. The proposed treatment, integrated with the face of the patient, was presented before clinical treatment. The patient was rehabilitated with ceramic veneers. The virtual design contributed to a satisfactory and predictable esthetic outcome.

Artificial immune systems applied to fault detection and isolation: A brief review of immune response-based approaches and a case study

Graphical abstractDisplay Omitted HighlightsWe review some approaches inspired on infectious nonself and danger models.Novel immune-inspired algorithms tend to rely more on expert knowledge.Reviewed approaches can be applied to a fault detection benchmark.Experimental results show fault detection with no false alarms.A fault isolation mechanism can be provided from class ambiguity measurements. This paper aims to document the application of a new generation of artificial immune systems (AIS) in fault detection and isolation problems. These kind of algorithms are able to explore normal and anomalous behavior evidences, however, they may often require a more explicit prior knowledge provided by experts, usually difficult to obtain in some practical cases. Thus, many immune inspired approaches applied to fault detection and isolation (FDI) in the literature are based on negative selection algorithms. Considering these points, this work presents a review on three AIS approaches. Once reviewed and contextualized, the evaluated techniques are properly adjusted considering their main parameters and ways of processing data, and then, applied to a case study of fault detection and isolation in order to provide a performance analysis of these techniques, according to their applicability to these problems.

Intraoral Excision of a Huge Cheek Lipoma

Lipomas are benign tumors of mature adipocytes unusual in the oral and maxillofacial region. The average size of cheek lipomas in the literature ranges from 1.5 to 2.5 cm, with the maximum size of 5 cm. Their etiology remains unclear. Lipomas present, clinically, as well circumscribed, slow growing, painless masses, usually treated by complete excision. The aim of this paper is to present a 78-year-old Caucasian male patient with a huge cheek lipoma compromising facial esthetics and treated through an intraoral excision. Postoperative period was uneventful with no signs of recurrence. Concluding, the intraoral approach is a relatively simple technique that should be taken into account when considering the surgical removal of cheek lipomas.

Dendritic Cell Algorithm Applied to Ping Scan Investigation Revisited: Detection Quality and Performance Analysis

The dendritic cell algorithm is an immune inspired method based on the danger model, which relies on cell interactions to antigens and signals, considering the correlation between both events, to solve anomaly detection problems. Starting with new datasets, comprising ping scans and file transfers in computer networks, this paper proposes improvements in the algorithm test methodology and qualitative analysis. Results measurement, detection capability, and performance evaluation are explored and discussed, including a real-time analysis and a comparison with similar approaches. Concluding, the study discusses advantages and limitations of the studied approach, suggesting possible improvements and new applications.

Analysis of stresses during the polymerization shrinkage of self-curing resin cement in indirect restorations: A finite-element study

BACKGROUND Adhesive cementation is essential for the longevity of indirect esthetic restorations. However, polymerization shrinkage of resin cement generates stress, which may cause failures in the tooth-restoration interface. So, understanding of the biomechanics of resin cement is important for predicting the clinical behavior of an esthetic indirect restoration. AIMS To analyze the stresses generated during polymerization shrinkage of self-curing resin cement in ceramic and in indirect resin (IR) restorations, using the finite-element method (FEM). SETTINGS AND DESIGN Numerical study using the finite-element analysis. MATERIALS AND METHODS A three-dimensional (3D) model of a second molar restored with ceramic or IR onlay restoration was designed. The polymerization shrinkage of self-curing resin cement was simulated in FEM software using an analogy between the thermal stress and the resulting contraction of the resin cement. The localization and values of tensile stresses in the dental structure, cement, and adhesive layer were identified. RESULTS The location and value of the tensile stresses were similar for the two restorative materials. High tensile stresses were identified in the axiopulpal wall and angles of the tooth preparation, with the major stresses found in the cement located in the axiopulpal wall. CONCLUSIONS The high stresses values and their concentration in the angles of the prepared tooth emphasize the importance of round angles and the use of cements with lower rates of shrinkage.