Online recognition of sketched arrow-connected diagrams

We introduce a new, online, stroke-based recognition system for hand-drawn diagrams which belong to a group of documents with an explicit structure obvious to humans but only loosely defined from the machine point of view. We propose a model for recognition by selection of symbol candidates, based on evaluation of relations between candidates using a set of predicates. It is suitable for simpler structures where the relations are explicitly given by symbols, arrows in the case of diagrams. Knowledge of a specific diagram domain is used—the two domains are flowcharts and finite automata. Although the individual pipeline steps are tailored for these, the system can readily be adapted for other domains. Our entire diagram recognition pipeline is outlined. Its core parts are text/non-text separation, symbol segmentation, their classification and structural analysis. Individual parts have been published by the authors previously and so are described briefly and referenced. Thorough evaluation on benchmark databases shows the accuracy of the system reaches the state of the art and is ready for practical use. The paper brings several contributions: (a) the entire system and its state-of-the-art performance; (b) the methodology exploring document structure when it is loosely defined; (c) the thorough experimental evaluation; (d) the new annotated database for online sketched flowcharts and finite automata diagrams.     

Business Intelligence Acceptance: The Prominence of Organizational Factors

The specifics of business intelligence systems compared to operational IS motivate the necessity to research the business intelligence systems acceptance determinants separately. The authors followed an exploratory approach in order to conceptualize a business intelligence acceptance model. Their findings show that in the Business Intelligence Systems context, there is a significant emphasis on organizational factors, such as result demonstrability, social influence, and facilitating conditions with sufficient resources that help build an adequate information culture all substantially influencing the effective acceptance of business intelligence systems.     

Small‐signal and noise modeling of class of HEMTs using knowledge‐based artificial neural networks

In this article, the neural network approach is exploited for development of bias‐dependent small‐signal and noise models of a class of microwave field effect transistor (FETs) made in the same technology but differing in the gate width. The prior knowledge neural approach is applied. Introducing gate width at the input of proposed neural networks, as well as the S/noise parameters of a device that belongs to the same class as the modeled device representing the prior knowledge, leads to very accurate scattering and noise parameters' modeling, as exemplified by modeling of class of pseudomorphic high electron mobility transistor (pHEMT) devices. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Limitations of a Mapping Algorithm with Fragmentation Mimics (MAFM) when modeling statistical data sources based on measured packet network traffic

Knowing the estimation of a statistical process’s parameters for measured network traffic is very important as it can then be further used for the statistical analyses and modeling of network traffic in simulation tools. It is for this reason that different estimation methods are proposed that allow estimations of the statistical processes of network traffic. One of them is our own histograms comparison (EMHC) based method that can be used to estimate statistical data-length process parameters from measured packet traffic. The main part of EMHC method is Mapping Algorithm with Fragmentation Mimics (MAFM).     

Disquiet in the plasma

The metaphor of plasma is taken up to present and discuss movement and engagement by participants in mixed reality installation arts. Two works involving full body video portraits exhibited through large plasma screens in a variety of public settings are covered. Machinic mediations of video realism are considered in terms of embodied interaction in which viewer-participants contribute to the ‘disquiet’ of gendered figuring. Processural, proximal and personal aspects of responsive engagement are discussed. This is extended to performativity that may lead us to critical reflection of our own actions and responses in mixed reality arts.     

Efficient SAT-based bounded model checking for software verification

This paper discusses our methodology for formal analysis and automatic verification of software programs. It is applicable to a large subset of the C programming language that includes pointer arithmetic and bounded recursion. We consider reachability properties, in particular whether certain assertions or basic blocks are reachable in the source code, or whether certain standard property violations can occur. We perform this analysis via a translation to a Boolean circuit representation based on modeling basic blocks. The program is then analyzed by a back-end SAT-based bounded model checker, where each unrolling is mapped to one step in a block-wise execution of the program.     

Extension of domains of states

We deal with categorical aspects of the extensions of generalized probability measures. In particular, we study various domains of fuzzy sets, describe the relationships between σ-fields of crisp sets and generated Łukasiewicz tribes of measurable functions, and mention some probabilistic aspects. D-posets and sequential continuity play an important role. This work was supported by the Slovak Research and Development Agency under the contract No. APVV-0071-06, Protocol for Scientific and Technological Collaboration between the Republic of Italy and Slovak Republic, Project No. 15: Algebraic and Logical Systems of Soft Computing, and VEGA 2/6088/26.     

Thermal images generated by a line-scanning technique: statistical properties

The analysis of statistical parameters of computer-generated therfial images by a line-scanning technique indicates an approach to efficient image transmission.     

Mode-selective dynamic light scattering: theory versus experimental realization

We present a quantitative experimental comparison of fiber-based, single- and few-mode dynamic light scattering with the classical pinhole-detection optics. The recently presented theory of mode-selective dynamic light scattering [Appl. Opt. 32, 2860 (1993)] predicts a collection efficiency and a signal-tobaseline ratio superior to that of a classical pinhole setup. These predictions are confirmed by our experiments. Using single-mode optical fibers with different cutoff wavelengths and commercially available mechanical components, we have constructed a mode-selective detection optics in a simple and compact dynamic light-scattering spectrometer that permits an optimal compromise between signal intensity and dynamical resolution.