Ensuring primary realization of pressure unit in the vacuum range without typically utilized static expansion system

After the break-up of Czechoslovakia in 1993 the primary metrological standards authority almost fully remained in Slovakia. So we had to build our primary vacuum metrology anew. But we could do it using uptodate techniques that are more effective and they enable us to fulfil our task more effectively and in a shorter time.The steady demand to widen the lower pressure range and a steady demand for maximal accuracy collide with the financial possibilities open to a small country. So it is impossible to follow the classical pattern for the vacuum standards: liquid columns, static expansion system and dynamic expansion system. But it is possible to utilize contemporary progress in construction of piston manometers. This enables us to discard liquid column and static expansion techniques in favour of piston technique [Tesar J, Prazak D. Vacuum 2002; 67: 311, Tesar J, Prazak D, Krajicek Z. In:Proceedings of international symposium on Pressure and Vacuum, 2003. p. 169, Tesar J, Repa P, Prazak D, Krajicek Z, Peksa L. Vacuum 2004; 76: 491.]. Such system fulfils all the needs of a little industrial country and is economically acceptable.     

Catalyst instabilities during the liquid phase partial oxidation of methane

A promising catalytic system for the low temperature oxidation of methane to a methanol derivative has been investigated under both batch and semi-continuous operation in two different reactor types. The system comprises of a bimetallic palladium and copper(II) chloride catalyst contained in a trifluoroacetic acid (TFA) and an aqueous phase. Methane, oxygen and a co-reductant carbon monoxide constitute the gas phase. Typical operating conditions were a temperature of 85 °C and a pressure of 83 bar.

The yields of the methyl trifluoroacetate product observed in this present work were less than those obtained in other batch autoclave works, which employed only 4 ml of liquid phase, compared with 50 ml in this study. Furthermore, an encouraging initial product formation rate of ca. 40 mol/m³ h, quickly decreased after the first hour, and came to an apparent end after only 2 h. This observation had not been reported previously.

Work performed in a semi-continuous porous tube reactor (300 ml of re-circulating liquid phase) also showed the same reaction characteristics as in the batch reactor. Thus, the deteriorating product formation rate cannot be attributed to gaseous reactant depletion (batch operation). The results suggest problems associated with catalyst instabilities, e.g. with the previously elucidated Wacker chemistry.     

Testability-analysis driven test-generation of analogue cores

A new definition of the testability transfer factor for circuit components that provides better sensitivity with respect to parametric deviations is presented. New equations for the testability measures in a mixed-signal core are given. Testability analysis is used for test-pattern generation and for consideration of inserting wrapper cells. The simulation results show the effectiveness of the approach.     

Analysis of Interconnected Oscillators by Dissipativity Theory

This paper employs dissipativity theory for the global analysis of limit cycles in particular dynamical systems of possibly high dimension. Oscillators are regarded as open systems that satisfy a particular dissipation inequality. It is shown that this characterization has implications for the global stability analysis of limit cycle oscillations: i) in isolated oscillators, ii) in interconnections of oscillators, and iii) for the global synchrony analysis in interconnections of identical oscillators     

HotSpot: a compact thermal modeling methodology for early-stage VLSI design

This paper presents HotSpot-a modeling methodology for developing compact thermal models based on the popular stacked-layer packaging scheme in modern very large-scale integration systems. In addition to modeling silicon and packaging layers, HotSpot includes a high-level on-chip interconnect self-heating power and thermal model such that the thermal impacts on interconnects can also be considered during early design stages. The HotSpot compact thermal modeling approach is especially well suited for preregister transfer level (RTL) and presynthesis thermal analysis and is able to provide detailed static and transient temperature information across the die and the package, as it is also computationally efficient.     

Mechanistic Insight in the Ethane Dehydrogenation Reaction over Cr/Al2O3 Catalysts

A Cr/Al₂O₃ alkane dehydrogenation catalyst exhibits a maximum in ethylene yield during an ethane dehydrogenation cycle. Isotopic labelling experiments with monolabelled ¹³C-ethane and deuterium were used to elucidate whether the initial activity increase could be due to formation of an active, larger hydrocarbon intermediate on the surface. The results strongly indicate that this is not the case, and instead point to a traditional reaction cycle involving adsorption of ethane to form an ethyl species, followed by desorption of ethene and hydrogen. Transient kinetic data suggest that ethane adsorption is the rate-determining step of reaction.     

Face detection by structural models

Despite the successes in the last two decades, the state-of-the-art face detectors still have problems in dealing with images in the wild due to large appearance variations. Instead of leaving appearance variations directly to statistical learning algorithms, we propose a hierarchical part based structural model to explicitly capture them. The model enables part subtype option to handle local appearance variations such as closed and open month, and part deformation to capture the global appearance variations such as pose and expression. In detection, candidate window is fitted to the structural model to infer the part location and part subtype, and detection score is then computed based on the fitted configuration. In this way, the influence of appearance variation is reduced. Besides the face model, we exploit the co-occurrence between face and body, which helps to handle large variations, such as heavy occlusions, to further boost the face detection performance. We present a phrase based representation for body detection, and propose a structural context model to jointly encode the outputs of face detector and body detector. Benefit from the rich structural face and body information, as well as the discriminative structural learning algorithm, our method achieves state-of-the-art performance on FDDB, AFW and a self-annotated dataset, under wide comparisons with commercial and academic methods.     

On the Relation of Job Insecurity,Job Autonomy,Innovative Work Behaviour and the Mediating Effect of Work Engagement

European policy is focusing on innovation as a way out of the economic crisis. At the same time, job insecurity is rising as Europe is still in crisis. In this paper, we examine whether job insecurity affects the innovative work behaviour of employees by focusing on the relation between job insecurity, job autonomy, work engagement and innovative work behaviour (IWB). Using employee level survey data, we use structural equation modelling to disentangle the relations between these variables. The partially mediated model shows the best fit with the data. This model shows that job insecurity and autonomy are both directly and indirectly, through work engagement, related with IWB. For autonomy these relations are positive, while they are negative (and smaller) for job insecurity. Moreover, a negative covariance is observed between job insecurity and autonomy.     

Classification of semantic relations between nominals

The NLP community has shown a renewed interest in deeper semantic analyses, among them automatic recognition of semantic relations in text. We present the development and evaluation of a semantic analysis task: automatic recognition of relations between pairs of nominals in a sentence. The task was part of SemEval-2007, the fourth edition of the semantic evaluation event previously known as SensEval. Apart from the observations we have made, the long-lasting effect of this task may be a framework for comparing approaches to the task. We introduce the problem of recognizing relations between nominals, and in particular the process of drafting and refining the definitions of the semantic relations. We show how we created the training and test data, list and briefly describe the 15 participating systems, discuss the results, and conclude with the lessons learned in the course of this exercise.     

Iris segmentation in non-ideal images using graph cuts

A non-ideal iris image segmentation approach based on graph cuts is presented that uses both the appearance and eye geometry information. A texture measure based on gradients is computed to discriminate between eyelash and non-eyelash regions, combined with image intensity differences between the iris, pupil, and the background (region surrounding the iris) are utilized as cues for segmentation. The texture and intensity distributions for the various regions are learned from histogramming and explicit sampling of the pixels estimated to belong to the corresponding regions. The image is modeled as a Markov Random Field and the energy minimization is achieved via graph cuts to assign each image pixel one of the four possible labels: iris, pupil, background, and eyelash. Furthermore, the iris region is modeled as an ellipse, and the best fitting ellipse to the initial pixel based iris segmentation is computed to further refine the segmented region. As a result, the iris region mask and the parameterized iris shape form the outputs of the proposed approach that allow subsequent iris recognition steps to be performed for the segmented irises. The algorithm is unsupervised and can deal with non-ideality in the iris images due to out-of-plane rotation of the eye, iris occlusion by the eyelids and the eyelashes, multi-modal iris grayscale intensity distribution, and various illumination effects. The proposed segmentation approach is tested on several publicly available non-ideal near infra red (NIR) iris image databases. We compare both the segmentation error and the resulting recognition error with several leading techniques, demonstrating significantly improved results with the proposed technique.