Acoustic emission signal processing framework to identify fracture in aluminum alloys

Acoustic emission (AE) is a common nondestructive evaluation tool that has been used to monitor fracture in materials and structures. The direct connection between AE events and their source, however, is difficult because of material, geometry and sensor contributions to the recorded signals. Moreover, the recorded AE activity is affected by several noise sources which further complicate the identification process. This article uses a combination of in situ experiments inside the scanning electron microscope to observe fracture in an aluminum alloy at the time and scale it occurs and a novel AE signal processing framework to identify characteristics that correlate with fracture events. Specifically, a signal processing method is designed to cluster AE activity based on the selection of a subset of features objectively identified by examining their correlation and variance. The identified clusters are then compared to both mechanical and in situ observed microstructural damage. Results from a set of nanoindentation tests as well as a carefully designed computational model are also presented to validate the conclusions drawn from signal processing

Damage identification of brick masonry under cyclic loading based on acoustic emissions

Ageing infrastructure, such as masonry railway bridges, suffers from structural deterioration due to fatigue loading. This paper presents an experimental study of brick masonry deterioration under gradually increasing cyclic loading with the aid of Acoustic Emission (AE) sensors. Two masonry beams were tested in the laboratory under similar stress conditions that masonry arches experience during train loading. An in-house AE monitoring system was developed for this study allowing both feature-based and waveform-based AE analysis. In the lab tests, different modes of damage were activated, such as tensile bond failure, brick and mortar crushing, diagonal shear failure and joint sliding. Feature-based AE analysis shows an increase in cracking rate before brittle failure events that is not necessarily accompanied by an increase in deformation rate. Statistical analysis reveals clear trends in AE results that correlate to different damage stages. The paper discusses how these findings can be leveraged to develop real-time structural alert systems that could provide early warning of damage before a significant increase in dynamic deformation occurs

Fracture Evaluation of Multi-layered Precast Reinforced Geopolymer-Concrete Composite Beams by Incorporating Acoustic Emission into Mechanical Analysis

In this study, a multi-layered steel reinforced composite beams which are composed of geopolymer concrete section at tensile zone and Portland cement based concrete at compression are investigated. The beams were tested to failure to compare the toughness, post peak behaviour and failure mode based on the variation of the depth of layers. The mechanical analysis incorporated into acoustic emission technique showed that the geopolymer beam endured more deflection than the ordinary Portland cement based beams, however their ultimate load carrying capacities were quite similar. Further, the composite beams, resulted in transition of failure mode of shear to a flexural

Learning to Predict Clinical Outcomes from Soft Tissue Sarcoma MRI

Soft Tissue Sarcomas (STS) are among the most dangerous diseases, with a 50% mortality rate in the USA in 2016. Heterogeneous responses to the treatments of the same sub-type of STS as well as intra-tumor heterogeneity make the study of biopsies imprecise. Radiologists make efforts to find non-invasive approaches to gather useful and important information regarding characteristics and behaviors of STS tumors, such as aggressiveness and recurrence. Quantitative image analysis is an approach to integrate information extracted using data science, such as data mining and machine learning with biological an clinical data to assist radiologists in making the best recommendation on clinical trials and the course of treatment. The new methods in “Radiomics extract meaningful features from medical imaging data for diagnostic and prognostic goals. Furthermore, features extracted from Convolutional Neural Networks (CNNs) are demonstrating very powerful and robust performance in computer aided decision systems (CADs). Also, a well-known computer vision approach, Bag of Visual Words, has recently been applied on imaging data for machine learning purposes such as classification of different types of tumors based on their specific behavior and phenotype. These approaches are not fully and widely investigated in STS. This dissertation provides novel versions of image analysis based on Radiomics and Bag of Visual Words integrated with deep features to quantify the heterogeneity of entire STS as well as sub-regions, which have predictive and prognostic imaging features, from single and multi-sequence Magnetic Resonance Imaging (MRI). STS are types of cancer which are rarely touched in term of quantitative cancer analysis versus other type of cancers such as lung, brain and breast cancers. This dissertation does a comprehensive analysis on available data in 2D and multi-slice to predict the behavior of the STS with regard to clinical outcomes such as recurrence or metastasis and amount of tumor necrosis. The experimental results using Radiomics as well as a new ensemble of Bags of Visual Words framework are promising with 91.66% classification accuracy and 0.91 AUC for metastasis, using ensemble of Bags of Visual Words framework integrated with deep features, and 82.44% classification accuracy with 0.63 AUC for necrosis progression, using Radiomics framework, in tests on the available datasets

Detection of onset of failure in prestressed strands by cluster analysis of acoustic emissions

Corrosion of prestressed concrete structures is one of the main challenges that engineers face today. In response to this national need, this paper presents the results of a long-term project that aims at developing a structural health monitoring (SHM) technology for the nondestructive evaluation of prestressed structures. In this paper, the use of permanently installed low profile piezoelectric transducers (PZT) is proposed in order to record the acoustic emissions (AE) along the length of the strand. The results of an accelerated corrosion test are presented and k-means clustering is applied via principal component analysis (PCA) of AE features to provide an accurate diagnosis of the strand health. The proposed approach shows good correlation between acoustic emissions features and strand failure. Moreover, a clustering technique for the identification of false alarms is proposed

Islamic Medicine Theory and agree views

طب اسلامی به عنوان یک مکتب دارای مبانی و اصول، ایدئولوژی، علوم پایه و منابع محکم است. در مقاله حاضر با دیدگاهی بی‌طرفانه و بدون قضاوت در مورد درستی یا نادرستی گزاره‌ها، به طبقه‌بندی دیدگاه‌های موافق مکتب طب اسلامی پرداخته و این دیدگاه‌ها در 7 عنوان طبقه‌بندی گردید. امروزه آثار نوشتاری از قبیل کتب، مقالات و مطالب فراوانی با عنوان طب اسلامی منتشر می‌شوند و اصالت علمی و غنای محتوایی لازم در برخی آثار مشاهده نمی‌گردد و به نظر می‌رسد در برخی آثار بدون رعایت معیارهای علمی به طرح موضوع طب اسلامی پرداخته شده است. از این رو در این مقاله، از برخی آثار که در مقایسه با دیگران، از غنای علمی و محتوایی بیشتری برخوردار بودند، استفاده گردید. با بررسی دیدگاه‌های موافق مکتب طب اسلامی به روشنی قابل استنباط است که در مورد تعریف و مفهوم‌شناسی طب اسلامی، دیدگاه‌های مختلفی وجود دارد. به نظر می‌رسد اختلاف دیدگاه‌ها، عمدتاً مربوط به زاویه دید و نگرش پژوهشگران به مقوله طب اسلامی است و یکی از دلایل گستردگی و پراکندگی دیدگاه‌ها، استفاده‌نکردن از روش‌های علمی مباحثه و تدوین نظریه علمی است که استفاده از روش تحقیق مناسب را جهت شکل‌گیری دیدگاهی جامع ضروری می‌سازد.The Islamic medicine as a Theory, has principles, ideology, science and sturdy materials. IN this article, with unbiased and non-judgmental comment about True or false statements, we classify agree views about Islamic medicine Theory in 7 title.Nowadays, lots of Books, articles and Subjects has published as Islamic medicine. But scientific originality and richness of content is not observed in some works. Therefore in this article, we used some richer subjects in terms of content. By examining the agree views about Islamic medicine Theory, Clearly be deduced that There are several views about definition and concept of Islamic medicine. It appears that differences of opinion, mainly due to the viewing angle and researchers attitude to the issue of Islamic medicine. One of the reasons for the extent and distribution of ideas is not using the scientific method by researchers. Thus, using proper research method is essential for the formation of a comprehensive view