Featurebased method for document alignment in comparable news corpora

In this paper, we present a feature-based method to align documents with similar content across two sets of bilingual comparable corpora from daily news texts. We evaluate the contribution of each individual feature and investigate the incorporation of these diverse statistical and heuristic features for the task of bilingual document alignment. Experimental results on the English-Chinese and English-Malay comparable news corpora show that our proposed Discrete Fourier Transformbased term frequency distribution feature is very effective. It contributes 4.1 % and 8 % to performance improvement over Pearson’s correlation method on the two comparable corpora. In addition, when more heuristic and statistical features as well as a bilingual dictionary are utilized, our method shows an absolute performance improvement of 23.2% and 15.3 % on the two sets of bilingual corpora when comparing with a prior information retrieval-based method.

Study on Wideband THz Backward Wave Oscillator Driven by Pseudospark-Sourced Sheet Electron Beam

A backward wave oscillator (BWO) based on a double-staggered grating (DSG) slow wave structure (SWS) is investigated as a high-power wideband terahertz (THz) source, driven by a sheet electron beam emitting from a pseudospark plasma cathode. First, the DSG SWS is optimized in simulation to have a suitable dispersion characteristic. Then, the BWO with a wideband output structure consisting of a tapered section of DSG and an L-shaped connector is modeled under an operating voltage of 24-38 kV and a current density of 2- 5\times 10 {{7}} A/m 2 (beam current of 1.5-3.8 A). A maximum power of 3.9 kW is obtained, and a wide bandwidth of over 38 GHz (343-381 GHz) is achieved. The impact of fabricating errors of the SWS on the performance of the BWO is analyzed in simulation. The effects of the plasma in the interaction space on the BWO performance are also analyzed, showing that the plasma causes an increase in the oscillation frequency by 1.0-1.2

A computational model of spatio-temporal cardiac intracellular calcium handling with realistic structure and spatial flux distribution from sarcoplasmic reticulum and t-tubule reconstructions

Intracellular calcium cycling is a vital component of cardiac excitation-contraction coupling. The key structures responsible for controlling calcium dynamics are the cell membrane (comprising the surface sarcolemma and transverse-tubules), the intracellular calcium store (the sarcoplasmic reticulum), and the co-localisation of these two structures to form dyads within which calcium-induced-calcium-release occurs. The organisation of these structures tightly controls intracellular calcium dynamics. In this study, we present a computational model of intracellular calcium cycling in three-dimensions (3-D), which incorporates high resolution reconstructions of these key regulatory structures, attained through imaging of tissue taken from the sheep left ventricle using serial block face scanning electron microscopy. An approach was developed to model the sarcoplasmic reticulum structure at the whole-cell scale, by reducing its full 3-D structure to a 3-D network of one-dimensional strands. The model reproduces intracellular calcium dynamics during control pacing and reveals the high-resolution 3-D spatial structure of calcium gradients and intracellular fluxes in both the cytoplasm and sarcoplasmic reticulum. We also demonstrated the capability of the model to reproduce potentially pro-arrhythmic dynamics under perturbed conditions, pertaining to calcium-transient alternans and spontaneous release events. Comparison with idealised cell models emphasised the importance of structure in determining calcium gradients and controlling the spatial dynamics associated with calcium-transient alternans, wherein the probabilistic nature of dyad activation and recruitment was constrained. The model was further used to highlight the criticality in calcium spark propagation in relation to inter-dyad distances. The model presented provides a powerful tool for future investigation of structure-function relationships underlying physiological and pathophysiological intracellular calcium handling phenomena at the whole-cell. The approach allows for the first time direct integration of high-resolution images of 3-D intracellular structures with models of calcium cycling, presenting the possibility to directly assess the functional impact of structural remodelling at the cellular scale

Analysis of cybersecurity threats in Industry 4.0: the case of intrusion detection

Nowadays, industrial control systems are experiencing a new revolution with the interconnection of the operational equipment with the Internet, and the introduction of cutting-edge technologies such as Cloud Computing or Big data within the organization. These and other technologies are paving the way to the Industry 4.0. However, the advent of these technologies, and the innovative services that are enabled by them, will also bring novel threats whose impact needs to be understood. As a result, this paper provides an analysis of the evolution of these cyber-security issues and the requirements that must be satis ed by intrusion detection defense mechanisms in this context.Springer ; Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Real-time Experimental Demonstration of Timestamped Digitised Radio over Switched Optical Ethernet Fronthaul

This paper experimentally demonstrates a novel digitised RF service transmission with data compression over switched 10Gbps optical Ethernet fronthaul showing low latency (<2.4µs), high transmission efficiency (~1/3 that of CPRI) and wide dynamic range (40dB)

Recombining your way out of trouble: The genetic architecture of hybrid fitness under environmental stress

Hybridization between species can either promote or impede adaptation. But there is a deficit in our understanding of the genetic basis of hybrid fitness, especially in non-domesticated organisms, and when populations are facing environmental stress. We made genetically variable F2 hybrid populations from two divergent Saccharomyces yeast species. We exposed populations to ten toxins and sequenced the most resilient hybrids on low coverage using ddRADseq to investigate four aspects of their genomes: 1) hybridity, 2) interspecific heterozygosity, 3) epistasis (positive or negative associations between non-homologous chromosomes) and 4) ploidy. We used linear mixed effect models and simulations to measure to which extent hybrid genome composition was contingent on the environment. Genomes grown in different environments varied in every aspect of hybridness measured, revealing strong genotype-environment interactions. We also found selection against heterozygosity or directional selection for one of the parental alleles, with larger fitness of genomes carrying more homozygous allelic combinations in an otherwise hybrid genomic background. In addition, individual chromosomes and chromosomal interactions showed significant species biases and pervasive aneuploidies. Against our expectations, we observed multiple beneficial, opposite-species chromosome associations, confirmed by epistasis- and selection-free computer simulations, which is surprising given the large divergence of parental genomes (∼15%). Together, these results suggest that successful, stress-resilient hybrid genomes can be assembled from the best features of both parents without paying high costs of negative epistasis. This illustrates the importance of measuring genetic trait architecture in an environmental context when determining the evolutionary potential of genetically diverse hybrid populations

Machine Learning to Automate Network Segregation for Enhanced Security in Industry 4.0

The heavy reliance of Industry 4.0 on emerging communication technologies, notably Industrial Internet-of-Things (IIoT) and Machine-Type Communications (MTC), and the increasing exposure of these traditionally isolated infrastructures to the Internet, are tremendously increasing the attack surface. Network segregation is a viable solution to address this problem. It essentially splits the network into several logical groups (subnetworks) and enforces adequate security policy on each segment, e.g., restricting unnecessary intergroup communications or controlling the access. However, existing segregation techniques primarily depend on manual configurations, which renders them inefficient for cyber-physical production systems because they are highly complex and heterogeneous environments with massive number of communicating machines. In this paper, we incorporate machine learning to automate network segregation, by efficiently classifying network end-devices into several groups through examining the traffic patterns that they generate. For performance evaluation, we analysed the data collected from a large segment of Infineon’s network in the context of the EU funded ECSEL-JU project “SemI40”. In particular, we applied feature selection and trained several supervised learning algorithms. Test results, using 10-fold cross validation, revealed that the algorithms generalise very well and achieve an accuracy up to 99.4%

Towards an Integrative Cognitive-Socio-Technical Approach in Health Informatics: Analyzing Technology-Induced Error Involving Health Information Systems to Improve Patient Safety

The purpose of this paper is to argue for an integration of cognitive and socio-technical approaches to assessing the impact of health information systems. Historically, health informatics research has examined the cognitive and socio-technical aspects of health information systems separately. In this paper we argue that evaluations of health information systems should consider aspects related to cognition as well as socio-technical aspects including impact on workflow (i.e. an integrated view). Using examples from the study of technology-induced error in healthcare, we argue for the use of simulations to evaluate the cognitive-socio-technical impacts of health information technology [36]. Implications of clinical simulations and analysis of cognitive-social-technical impacts are discussed within the context of the system development life cycle to improve health information system design, implementation and evaluation