Identifying microphone from noisy recordings by using representative instance one class-classification approach

Rapid growth of technical developments has created huge challenges for microphone forensics - a subcategory of audio forensic science, because of the availability of numerous digital recording devices and massive amount of recording data. Demand for fast and efficient methods to assure integrity and authenticity of information is becoming more and more important in criminal investigation nowadays. Machine learning has emerged as an important technique to support audio analysis processes of microphone forensic practitioners. However, its application to real life situations using supervised learning is still facing great challenges due to expensiveness in collecting data and updating system. In this paper, we introduce a new machine learning approach which is called One-class Classification (OCC) to be applied to microphone forensics; we demonstrate its capability on a corpus of audio samples collected from several microphones. In addition, we propose a representative instance classification framework (RICF) that can effectively improve performance of OCC algorithms for recording signal with noise. Experiment results and analysis indicate that OCC has the potential to benefit microphone forensic practitioners in developing new tools and techniques for effective and efficient analysis. © 2012 Academy Publisher

Large-scale exploration of neural relation classification architectures

Experimental performance on the task of relation classification has generally improved using deep neural network architectures. One major drawback of reported studies is that individual models have been evaluated on a very narrow range of datasets, raising questions about the adaptability of the architectures, while making comparisons between approaches difficult. In this work, we present a systematic large-scale analysis of neural relation classification architectures on six benchmark datasets with widely varying characteristics. We propose a novel multi-channel LSTM model combined with a CNN that takes advantage of all currently popular linguistic and architectural features. Our ‘Man for All Seasons’ approach achieves state-of-the-art performance on two datasets. More importantly, in our view, the model allowed us to obtain direct insights into the continued challenges faced by neural language models on this task. Example data and source code are available at: https://github.com/aidantee/ MASS.MR

Making tourist guidance systems more intelligent, adaptive and personalised using crowd sourced movement data

Ambient intelligence (AmI) provides adaptive, personalized, intelligent, ubiquitous and interactive services to wide range of users. AmI can have a variety of applications, including smart shops, health care, smart home, assisted living, and location-based services. Tourist guidance is one of the applications where AmI can have a great contribution to the quality of the service, as the tourists, who may not be very familiar with the visiting site, need a location-aware, ubiquitous, personalised and informative service. Such services should be able to understand the preferences of the users without requiring the users to specify them, predict their interests, and provide relevant and tailored services in the most appropriate way, including audio, visual, and haptic. This paper shows the use of crowd sourced trajectory data in the detection of points of interests and providing ambient tourist guidance based on the patterns recognised over such data

The Effect of Human Factor H on Immunogenicity of Meningococcal Native Outer Membrane Vesicle Vaccines with Over-Expressed Factor H Binding Protein

The binding of human complement inhibitors to vaccine antigens in vivo could diminish their immunogenicity. A meningococcal ligand for the complement down-regulator, factor H (fH), is fH-binding protein (fHbp), which is specific for human fH. Vaccines containing recombinant fHbp or native outer membrane vesicles (NOMV) from mutant strains with over-expressed fHbp are in clinical development. In a previous study in transgenic mice, the presence of human fH impaired the immunogenicity of a recombinant fHbp vaccine. In the present study, we prepared two NOMV vaccines from mutant group B strains with over-expressed wild-type fHbp or an R41S mutant fHbp with no detectable fH binding. In wild-type mice in which mouse fH did not bind to fHbp in either vaccine, the NOMV vaccine with wild-type fHbp elicited 2-fold higher serum IgG anti-fHbp titers (P = 0.001) and 4-fold higher complement-mediated bactericidal titers against a PorA-heterologous strain than the NOMV with the mutant fHbp (P = 0.003). By adsorption, the bactericidal antibodies were shown to be directed at fHbp. In transgenic mice in which human fH bound to the wild-type fHbp but not to the R41S fHbp, the NOMV vaccine with the mutant fHbp elicited 5-fold higher serum IgG anti-fHbp titers (P = 0.002), and 19-fold higher bactericidal titers than the NOMV vaccine with wild-type fHbp (P = 0.001). Thus, in mice that differed only by the presence of human fH, the respective results with the two vaccines were opposite. The enhanced bactericidal activity elicited by the mutant fHbp vaccine in the presence of human fH far outweighed the loss of immunogenicity of the mutant protein in wild-type animals. Engineering fHbp not to bind to its cognate complement inhibitor, therefore, may increase vaccine immunogenicity in humans

Monoclonal Antibodies to Meningococcal Factor H Binding Protein with Overlapping Epitopes and Discordant Functional Activity

Background: Meningococcal factor H binding protein (fHbp) is a promising vaccine candidate. Anti-fHbp antibodies can bind to meningococci and elicit complement-mediated bactericidal activity directly. The antibodies also can block binding of the human complement down-regulator, factor H (fH). Without bound fH, the organism would be expected to have increased susceptibility to bacteriolysis. Here we describe bactericidal activity of two anti-fHbp mAbs with overlapping epitopes in relation to their different effects on fH binding and bactericidal activity. Methods and Principal Findings: Both mAbs recognized prevalent fHbp sequence variants in variant group 1. Using yeast display and site-specific mutagenesis, binding of one of the mAbs (JAR 1, IgG3) to fHbp was eliminated by a single amino acid substitution, R204A, and was decreased by K143A but not by R204H or D142A. The JAR 1 epitope overlapped that of previously described mAb (mAb502, IgG2a) whose binding to fHbp was eliminated by R204A or R204H substitutions, and was decreased by D142A but not by K143A. Although JAR 1 and mAb502 appeared to have overlapping epitopes, only JAR 1 inhibited binding of fH to fHbp and had human complement-mediated bactericidal activity. mAb502 enhanced fH binding and lacked human complement-mediated bactericidal activity. To control for confounding effects of different mouse IgG subclasses on complement activation, we created chimeric mAbs in which the mouse mAb502 or JAR 1 paratopes were paired with human IgG1 constant regions. While both chimeric mAbs showed similar binding to fHbp, only JAR 1, whic

Meningococcal Factor H Binding Proteins in Epidemic Strains from Africa: Implications for Vaccine Development

Epidemics of meningococcal meningitis are common in sub-Saharan Africa. Most are caused by encapsulated serogroup A strains, which rarely cause disease in industrialized countries. A serogroup A polysaccharide protein conjugate vaccine recently was introduced in some countries in sub-Saharan Africa. The antibodies induced, however, may allow replacement of serogroup A strains with serogroup W-135 or X strains, which also cause epidemics in this region. Protein antigens, such as factor H binding protein (fHbp), are promising for prevention of meningococcal serogroup B disease. These proteins also are present in strains with other capsular serogroups. Here we report investigation of the potential of fHbp vaccines for prevention of disease caused by serogroup A, W-135 and X strains from Africa. Four fHbp amino acid sequence variants accounted for 81% of the 106 African isolates studied. While there was little cross-protective activity by antibodies elicited in mice by recombinant fHbp vaccines from each of the four sequence variants, a prototype native outer membrane vesicle (NOMV) vaccine from a mutant with over-expressed fHbp elicited antibodies with broad protective activity. A NOMV vaccine has the potential to supplement coverage by the group A conjugate vaccine and help prevent emergence of disease caused by non-serogroup A strains

The influence of personal and professional commitments on digitally disconnected experiences

In our ubiquitously connected world, it becomes more and more difficult to disconnect and leave all personal and professional commitments behind while on holiday. Mobile technology allows us to be connected wherever and whenever we want, but at the same time shifts expectations towards constant availability and responsiveness among friends and colleagues. Applying a qualitative research approach, we explored how social and professional commitments influence decisions and experiences of travelers that go on a digital-free holiday. Using the theoretical lens of surveillance, we found that travelers are digitally surveilled not only by their friends and family members on social media, but also by their superiors and colleagues through email and social networks. The expectations of being constantly available and responsive extend into their holiday, which makes it difficult for travelers to truly disconnect and enjoy their digital free travel experience. At the same time, they are inclined to engage in social surveillance of their peers which creates the constant urge to learn about any updates from their private and professional networks. We contribute to the tourism and information systems literature, by explaining how private and professional commitment influence the digital-free travel experience and extend the concept of surveillance to the work context