Anomaly diagnosis in ceramic claddings by thermography - A review

With the increasing importance given to building rehabilitation comes the need to create simple, fast and non-destructive testing methods (NDT) to identify problems and for anomaly diagnosis. Ceramic tiles are one of the most typical kinds of exterior wall cladding in several countries; the earliest known examples are Egyptian dating from 4000 BC. This type of building facade coating, though being quite often used in due to its aesthetic and architectural characteristics, is one of the most complex that can be applied given the several parts from which it is composed; hence, it is also one of the most difficult to correctly diagnose with expeditious methods. The detachment of ceramic wall tiles is probably the most common and difficult to identify anomaly associated with this kind of cladding and it is also definitely the one that can compromise security the most. Thus, it is necessary to study a process of inspection more efficient and economic than the currently used which often consist in semi-destructive methods (the most common is the pull off test), that can only be used in a small part of the building at a time, allowing some assumptions of what can the rest of the cladding be like. Infrared thermography (IRT) is a NDT with a wide variety of applications in building inspection that is becoming commonly used to identify anomalies related with thermal variations in the inspected surfaces. Few authors have studied the application of IRT in anomalies associated with ceramic claddings claiming that the presence of air or water beneath the superficial layer will influence the heat transfer in a way that can be detected in both a qualitative and a quantitative way by the thermal camera, providing information about the state of the wall in a much broad area per trial than other methods commonly used nowadays. This article intends to present a review of the state of art of this NDT and its potentiality in becoming a more efficient way to diagnose anomalies in ceramic wall claddings.

Open bite: diagnosis, treatment and stability

Open bite has fascinated Orthodontics due to the difficulties regarding its treatment and maintenance of results. This anomaly has distinct characteristics that, in addition to the complexity of multiple etiological factors, have aesthetic and functional consequences. Within this etiological context, several types of mechanics have been used in open bite treatment, such as palatal crib, orthopedic forces, occlusal adjustment, orthodontic camouflage with or without extraction, orthodontic intervention using mini-implants or mini-plates, and even orthognathic surgery. An accurate diagnosis and etiological determination are always the best guides to establish the objectives and the ideal treatment plan for such a malocclusion. This report describes two cases of open bite. At the end of the treatment, both patients had their canines and molars in Class I occlusion, normal overjet and overbite, and stability during the posttreatment period.

Characterization of Network-Wide Anomalies in Traffic Flows

Detecting and understanding anomalies in IP networks is an open and ill-defined problem. Toward this end, we have recently proposed the subspace method for anomaly diagnosis. In this paper we present the first large-scale exploration of the power of the subspace method when applied to flow traffic. An important aspect of this approach is that it fuses information from flow measurements taken throughout a network. We apply the subspace method to three different types of sampled flow traffic in a large academic network: multivariate timeseries of byte counts, packet counts, and IP-flow counts. We show that each traffic type brings into focus a different set of anomalies via the subspace method. We illustrate and classify the set of anomalies detected. We find that almost all of the anomalies detected represent events of interest to network operators. Furthermore, the anomalies span a remarkably wide spectrum of event types, including denial of service attacks (single-source and distributed), flash crowds, port scanning, downstream traffic engineering, high-rate flows, worm propagation, and network outage.

Mining Anomalies Using Traffic Feature Distributions

The increasing practicality of large-scale flow capture makes it possible to conceive of traffic analysis methods that detect and identify a large and diverse set of anomalies. However the challenge of effectively analyzing this massive data source for anomaly diagnosis is as yet unmet. We argue that the distributions of packet features (IP addresses and ports) observed in flow traces reveals both the presence and the structure of a wide range of anomalies. Using entropy as a summarization tool, we show that the analysis of feature distributions leads to significant advances on two fronts: (1) it enables highly sensitive detection of a wide range of anomalies, augmenting detections by volume-based methods, and (2) it enables automatic classification of anomalies via unsupervised learning. We show that using feature distributions, anomalies naturally fall into distinct and meaningful clusters. These clusters can be used to automatically classify anomalies and to uncover new anomaly types. We validate our claims on data from two backbone networks (Abilene and Geant) and conclude that feature distributions show promise as a key element of a fairly general network anomaly diagnosis framework.

Pregnancy as public property: The experience of couples following diagnosis of a foetal anomaly

Background: Pregnant women find themselves subject to comments and questions from people in public areas. Normally, becoming ‘public property’ is considered friendly and is relatively easy for pregnant women to deal with. However, following diagnosis of a fetal anomaly, the experience of being public property can exacerbate the emotional turmoil experienced by couples. Original research question: What is the experience of couples who continue pregnancy following the diagnosis of a fetal anomaly? Method: The study used an interpretive design informed by Merleau-Ponty and this paper reports on a subset of findings. Thirty-one interviews with pregnant women and their partners were undertaken following the diagnosis of a serious or lethal fetal anomaly. Women were between 25 and 38 weeks gestation at the time of their first interview. The non-directive interviews were audiotaped, transcribed verbatim and the transcripts were thematically analysed. Findings: A prominent theme that emerged during data analysis was that pregnancy is embodied therefore physically evident and ‘public’. Women found it difficult to deal with being public property when the fetus had a serious or lethal anomaly. Some women avoided social situations; others did not disclose the fetal condition but gave minimal or avoidant answers to minimise distress to themselves and others. The male participants were not visibly pregnant and they could continue life in public without being subject to the public’s gaze, but they were very aware and concerned about its impact on their partner. Conclusion: The public tend to assume that pregnancy is normal and will produce a healthy baby. This becomes problematic for women who have a fetus with an anomaly. Women use strategies to help them cope with becoming public property during pregnancy. Midwives can play an important role in reducing the negative consequences of a woman becoming public property following the diagnosis of a fetal anomaly.

Parents’ experience of time distortion following diagnosis of a serious or lethal fetal anomaly

PURPOSE: To explore the experience of couples who continued pregnancy following a diagnosis of serious or lethal fetal anomaly. STUDY DESIGN: Thirty-one male and female participants were recruited from a high-risk maternal–fetal medicine clinic in Washington State. Data were collected using in-depth interviews during pregnancy and after the birth of their baby. Transcribed interviews were thematically analyzed through the phenomenological lens of Merleau-Ponty. FINDINGS: Participants described how time became reconfigured and reconstituted as they tried to compress a lifetime of love for their future child into a limited period. Participants’ concepts of time became distorted and were related to their perceptual lived experience rather than the schedule-filled,regimented, linear clock time that governed the health professionals. CONCLUSION: Living in distorted time may be a mechanism parents use to cope with overwhelming and disorienting feelings when their unborn baby is diagnosed with a fetal anomaly.

A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.

Maternal coping, appraisals and adjustment following diagnosis of fetal anomaly.

OBJECTIVE: So far, associations between appraisals, maternal adjustment and coping following diagnosis of fetal anomaly have not been investigated in women who continue with their pregnancy. METHOD: This study measured maternal coping and adjustment after and appraisal of a diagnosis of fetal anomaly in 40 mothers who had continued with their pregnancy using a cross-sectional questionnaire design. RESULTS: Based on retrospective reporting, 35% of participants met full diagnostic criteria for post-traumatic stress disorder after having received the diagnosis. Women were significantly more depressed (p < 0.001) and anxious (p < 0.001) and reported significantly less positive affect (p < 0.05) after having received the diagnosis in comparison to the time after childbirth. There were no significant differences between emotion-focused and problem-focused coping. Stressful life events, women's age, number of people providing support and problem-focused coping explained 57.6% of variance in anxiety and depression after childbirth. Satisfaction with social support, emotion-focused coping and problem-focused coping significantly explained 40.6% of variance in positive affect after childbirth. CONCLUSION: Following a prenatal diagnosis and for the remainder of their pregnancy, particular attention should be paid to older mothers, those experiencing additional stressful life events and those who are socially isolated, as these women may experience greater distress after childbirth.

Rare chromosome abnormalities, prevalence and prenatal diagnosis rates from population-based congenital anomaly registers in Europe.

The aim of this study is to quantify the prevalence and types of rare chromosome abnormalities (RCAs) in Europe for 2000-2006 inclusive, and to describe prenatal diagnosis rates and pregnancy outcome. Data held by the European Surveillance of Congenital Anomalies database were analysed on all the cases from 16 population-based registries in 11 European countries diagnosed prenatally or before 1 year of age, and delivered between 2000 and 2006. Cases were all unbalanced chromosome abnormalities and included live births, fetal deaths from 20 weeks gestation and terminations of pregnancy for fetal anomaly. There were 10,323 cases with a chromosome abnormality, giving a total birth prevalence rate of 43.8/10,000 births. Of these, 7335 cases had trisomy 21,18 or 13, giving individual prevalence rates of 23.0, 5.9 and 2.3/10,000 births, respectively (53, 13 and 5% of all reported chromosome errors, respectively). In all, 473 cases (5%) had a sex chromosome trisomy, and 778 (8%) had 45,X, giving prevalence rates of 2.0 and 3.3/10,000 births, respectively. There were 1,737 RCA cases (17%), giving a prevalence of 7.4/10,000 births. These included triploidy, other trisomies, marker chromosomes, unbalanced translocations, deletions and duplications. There was a wide variation between the registers in both the overall prenatal diagnosis rate of RCA, an average of 65% (range 5-92%) and the prevalence of RCA (range 2.4-12.9/10,000 births). In all, 49% were liveborn. The data provide the prevalence of families currently requiring specialised genetic counselling services in the perinatal period for these conditions and, for some, long-term care.

Data mining and visualization for anomaly detection and diagnosis in civil structures

Peer reviewed

Application of machine learning technique in wind turbine fault diagnosis

In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.

Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

Tricuspid valve dysplasia and Ebstein's anomaly in dogs: case report

Dois casos de displasia da valva tricúspide são relatados neste trabalho. Os cães foram avaliados devido à fraqueza e presença de ascite. em ambos os casos, o exame ecocardiográfico mostrou insuficiência tricúspide e, em um deles, a inserção dos folhetos da valva tricúspide encontrava-se deslocada para baixo do ventrículo direito, caracterizando a anomalia de Ebstein. A terapia medicamentosa para insuficiência cardíaca congestiva foi iniciada, mas um dos animais veio a óbito subitamente alguns dias após o diagnóstico. O outro cão, apesar de inicialmente ter apresentado melhora significativa do quadro clínico, apresentou morte súbita. A necropsia dos animais revelou dilatação atrioventricular direita e folhetos tricúspides espessados. As características clínicas, métodos de diagnóstico e terapia medicamentosa são discutidas neste artigo.

Feelings of women regarding end-of-life decision making after ultrasound diagnosis of a lethal fetal malformation

Objective: this study investigated the feelings of women regarding end-of-life decision making after ultrasound diagnosis of a lethal fetal malformation. The aim of this study was to present the decision making process of women that chose for pregnancy termination and to present selected speeches of women about their feelings. Design: open psychological interviews conducted by a psychologist immediately after the diagnosis of fetal malformation by ultrasound. Analysis of the results was performed through a content analysis technique. Setting: the study was carried out at a public university hospital in Brazil. Participants: 249 pregnant women who had received the diagnosis of a severe lethal fetal malformation. Findings: fetal anencephaly was the most frequent anomaly detected in 135 cases (54.3%). Termination of pregnancy was decided by 172 (69.1%) patients and legally authorised by the judiciary (66%). The reason for asking for termination was to reduce suffering in all of them. In the 77 women who chose not to terminate pregnancy (30.9%), the reasons were related to feelings of guilt (74%). Key conclusions: the results support the importance of psychological counselling for couples when lethal fetal malformation is diagnosed. The act of reviewing moral and cultural values and elements of the unconscious provides assurance in the decision-making process and mitigates the risk of emotional trauma and guilt that can continue long after the pregnancy is terminated. (C) 2011 Elsevier Ltd. All rights reserved.

Heart failure in two West Highland white terriers caused by congenital angiomatous cardiac anomaly

The paper describes the clinical and pathological characteristics of an unusual cystic congenital cardiac anomaly that caused clinical signs of congestive heart failure, respiratory distress and cardiac arrhythmias in two West Highland white terrier puppies. In both dogs a definitive diagnosis was made postmortem.