Large volume metrology process model:measurability analysis with integration of metrology classification model and feature-based selection model

Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.

Genomic consequences of mating system evolution in the Pacific coastal dune endemic, Abronia umbellata (Nyctaginaceae)

The advent of next-generation sequencing has significantly reduced the cost of obtaining large-scale genetic resources, opening the door for genomic studies of non-model but ecologically interesting species. The shift in mating system, from outcrossing to selfing, has occurred thousands of times in angiosperms and is accompanied by profound changes in the population genetics and ecology of a species. A large body of work has been devoted to understanding why the shift occurs and the impact of the shift on the genetics of the resulting selfing populations, however, the causes and consequences of the transition to selfing involve a complicated interaction of genetic and demographic factors which are difficult to untangle. Abronia umbellata is a Pacific coastal dune endemic which displays a striking shift in mating system across its geographic range, with large-flowered outcrossing populations south of San Francisco and small-flowered selfing populations to the north. Abronia umbellata is an attractive model system for the study of mating system transitions because the shift appears to be recent and therefore less obscured by post-shift processes, it has a near one-dimensional geographic range which simplifies analysis and interpretation, and demographic data has been collected for many of the populations. In this study, we generated transcriptome-level data for 12 plants including individuals from both subspecies, along with a resequencing study of 48 individuals from populations across the range. The genetic analysis revealed a recent transition to selfing involving a drastic reduction in genetic diversity in the selfing lineage, potentially indicative of a recent population bottleneck and a transition to selfing due to reproductive assurance. Interestingly, the genetic structure of the populations was not coincident with the current subspecies demarcation, and two large-flowered populations were classified with the selfing subspecies, suggesting a potential need for re-evaluation of the current subspecies classification. Our finding of low diversity in selfing populations may also have implications for the conservation value of the threatened selfing subspecies.

The Ocean Economic Statistical System of China and Understanding of the Blue Economy

The ocean and its resources are increasingly seen as indispensable in addressing the multiple challenges the planet is facing in the decades to come. It has never been easy to quantify this particular sector of the economy, in any country, given the lack of a detailed, centralized data base with adequate specifics covering the necessary sectors, this article aims to compare the existing ocean economy statistical systems, especially Asia-Pacific, American and European countries, in order to overcome the deficiencies with regard to the diversity of definitions and statistical representations of ocean sectors, establish the standard statistical system and compile data for the global ocean economy.

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Threat analysis of IoT networks using artificial neural network intrusion detection system

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However, as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

'An Artificial Immune System as a Recommender System for Web Sites'

Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals' web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of the Open Directory Project as our ontology. This will then be used as the data for the Artificial Immune Systems rather than the actual addresses. The first attempt will involve using a simple classification code number coupled with the number of pages within that classification code. However, this implementation does not make use of the hierarchical tree-like structure of DMOZ. Consideration will then be given to the construction of a similarity measure for web profiles that makes use of this hierarchical information to build a better-informed Artificial Immune System.

Classification and clinical behavior of blastic plasmacytoid dendritic cell neoplasms according to their maturation-associated immunophenotypic profile

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare subtype of leukemia/lymphoma, whose diagnosis can be difficult to achieve due to its clinical and biological heterogeneity, as well as its overlapping features with other hematologic malignancies. In this study we investigated whether the association between the maturational stage of tumor cells and the clinico-biological and prognostic features of the disease, based on the analysis of 46 BPDCN cases classified into three maturation-associated subgroups on immunophenotypic grounds. Our results show that blasts from cases with an immature plasmacytoid dendritic cell (pDC) phenotype exhibit an uncommon CD56- phenotype, coexisting with CD34+ non-pDC tumor cells, typically in the absence of extramedullary (e.g. skin) disease at presentation. Conversely, patients with a more mature blast cell phenotype more frequently displayed skin/extramedullary involvement and spread into secondary lymphoid tissues. Despite the dismal outcome, acute lymphoblastic leukemia-type therapy (with central nervous system prophylaxis) and/or allogeneic stem cell transplantation appeared to be the only effective therapies. Overall, our findings indicate that the maturational profile of pDC blasts in BPDCN is highly heterogeneous and translates into a wide clinical spectrum -from acute leukemia to mature lymphoma-like behavior-, which may also lead to variable diagnosis and treatment.

'An Artificial Immune System as a Recommender System for Web Sites'

Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals' web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of the Open Directory Project as our ontology. This will then be used as the data for the Artificial Immune Systems rather than the actual addresses. The first attempt will involve using a simple classification code number coupled with the number of pages within that classification code. However, this implementation does not make use of the hierarchical tree-like structure of DMOZ. Consideration will then be given to the construction of a similarity measure for web profiles that makes use of this hierarchical information to build a better-informed Artificial Immune System.

Diagnóstico ecográfico de tumores anexiais: modelos do grupo international ovary tumor analysis (IOTA) versus classificação gynecologic imaging report and data system (GI-RADS)

A ecografia é o exame de primeira linha na identificação e caraterização de tumores anexiais. Foram descritos diversos métodos de diagnóstico diferencial incluindo a avaliação subjetiva do observador, índices descritivos simples e índices matematicamente desenvolvidos como modelos de regressão logística, continuando a avaliação subjectiva por examinador diferenciado a ser o melhor método de discriminação entre tumores malignos e benignos. No entanto, devido à subjectividade inerente a esta avaliação tornouse necessário estabelecer uma nomenclatura padronizada e uma classificação que facilitasse a comunicação de resultados e respectivas recomendações de vigilância. O objetivo deste artigo é resumir e comparar diferentes métodos de avaliação e classificação de tumores anexiais, nomeadamente os modelos do grupo International Ovary Tumor Analysis (IOTA) e a classificação Gynecologic Imaging Report and Data System (GI-RADS), em termos de desempenho diagnóstico e utilidade na prática clínica.

Insights into the Specificity of Thioredoxin Reductase-Thioredoxin Interactions. A Structural and Functional Investigation of the Yeast Thioredoxin System

The enzymatic activity of thioredoxin reductase enzymes is endowed by at least two redox centers: a flavin and a dithiol/disulfide CXXC motif. The interaction between thioredoxin reductase and thioredoxin is generally species-specific, but the molecular aspects related to this phenomenon remain elusive. Here, we investigated the yeast cytosolic thioredoxin system, which is composed of NADPH, thioredoxin reductase (ScTrxR1), and thioredoxin 1 (ScTrx1) or thioredoxin 2 (ScTrx2). We showed that ScTrxR1 was able to efficiently reduce yeast thioredoxins (mitochondrial and cytosolic) but failed to reduce the human and Escherichia coli thioredoxin counterparts. To gain insights into this specificity, the crystallographic structure of oxidized ScTrxR1 was solved at 2.4 angstrom resolution. The protein topology of the redox centers indicated the necessity of a large structural rearrangement for FAD and thioredoxin reduction using NADPH. Therefore, we modeled a large structural rotation between the two ScTrxR1 domains (based on the previously described crystal structure, PDB code 1F6M). Employing diverse approaches including enzymatic assays, site-directed mutagenesis, amino acid sequence alignment, and structure comparisons, insights were obtained about the features involved in the species-specificity phenomenon, such as complementary electronic parameters between the surfaces of ScTrxR1 and yeast thioredoxin enzymes and loops and residues (such as Ser(72) in ScTrx2). Finally, structural comparisons and amino acid alignments led us to propose a new classification that includes a larger number of enzymes with thioredoxin reductase activity, neglected in the low/high molecular weight classification.

Using health-related quality of life instruments for children with long-term conditions : On the basis of a national quality registry system

Introduction: There has been a continuous development of new technologies in healthcare that are derived from national quality registries. However, this innovation needs to be translated into the workflow of healthcare delivery, to enable children with long-term conditions to get the best support possible to manage their health during everyday life. Since children living with long-term conditions experience different interference levels in their lives, healthcare professionals need to assess the impact of care on children’s day-to-day lives, as a complement to biomedical assessments. Aim: The overall aim of this thesis was to explore and describe the use of instruments about health-related quality of life (HRQOL) in outpatient care for children with long-term conditions on the basis of a national quality registry system. Methods: The research was conducted by using comparative, cross-sectional and explorative designs and data collection was performed by using different methods. The questionnaire DISABKIDS Chronic Generic Measure -37 was used as well as semi-structured interviews and video-recordings from consultations. Altogether, 156 children (8–18 years) and nine healthcare professionals participated in the studies. Children with Type 1 Diabetes (T1D) (n 131) answered the questionnaire DISABKIDS and children with rheumatic diseases, kidney diseases and T1D (n 25) were interviewed after their consultation at the outpatient clinic after the web-DISABKIDS had been used. In total, nine healthcare professionals used the HRQOL instrument as an assessment tool during the encounters which was video-recorded (n 21). Quantitative deductive content analysis was used to describe content in different HRQOL instruments. Statistical inference was used to analyse results from DISABKIDS and qualitative content analysis was used to analyse the interviews and video-recordings. Results: The findings showed that based on a biopsychosocial perspective, both generic and disease-specific instruments should be used to gain a comprehensive evaluation of the child’s HRQOL. The DISABKIDS instrument is applicable when describing different aspects of health concerning children with T1D. When DISABKIDS was used in the encounters, children expressed positive experiences about sharing their results with the healthcare professional. It was discovered that different approaches led to different outcomes for the child when the healthcare professionals were using DISABKIDS during the encounter. When an instructing approach is used, the child’s ability to learn more about their health and how to improve their health is limited. When an inviting or engaging approach is used by the professional, the child may become more involved during the conversations. Conclusions: It could be argued that instruments of HRQOL could be used as a complement to biomedical variables, to promote a biopsychosocial perspective on the child’s health. According to the children in this thesis, feedback on their results after answering to web-DISABKIDS is important, which implies that healthcare professionals need to prioritize time for discussions about results from HRQOL instruments in the encounters. If healthcare professionals involve the child in the discussion of the results of the HRQOL, misinterpreted answers could be corrected during the conversation. Concurrently, this claims that healthcare professionals invite and engage the child.

Can birds play a role as High Nature Value indicators of montado system?

Montados form a heterogeneous landscape of wooded matrix dominated by cork and/or holm oak with open areas characterized by fuzzy boundaries. Montado supports a high biological diversity associated to low intensity management and a landscape diversity provided by a continuous gradient of land cover. Among other features this permits the classification of montados as a High Nature Value (HNV) system. We assessed the role of birds as HNV indicators for montado, and tested several bird groups—farmland, edge, forest generalists and forest specialists species; and some universal indicators such as species conservation status, Shannon’s diversity index and species richness. Our study areas covered the North–South distribution of cork oak in Portugal, and we surveyed the breeding bird communities across 117 sampling sites. In addition to variables related to management and sanitary status, we considered variables that characterize the landscape heterogeneity inside the montado—trees and shrub density and richness of woody vegetation. Our results suggest that specific bird guilds can be used as HNV indicators of particular typologies of montado, and highlight the need to develop an indicator that could be transversally applied to all types of montado.

Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.

Using linear algebra for protein structural comparison and classification.

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.