On requirement verification for evolving Statecharts specifications

Software development processes have been evolving from rigid, pre-specified, and sequential to incremental, and iterative. This evolution has been dictated by the need to accommodate evolving user requirements and reduce the delay between design decision and feedback from users. Formal verification techniques, however, have largely ignored this evolution and even when they made enormous improvements and found significant uses in practice, like in the case of model checking, they remained confined into the niches of safety-critical systems. Model checking verifies if a system’s model \(\mathcal{M}\) satisfies a set of requirements, formalized as a set of logic properties \(\Phi\) . Current model-checking approaches, however, implicitly rely on the assumption that both the complete model \(\mathcal{M}\) and the whole set of properties \(\Phi\) are fully specified when verification takes place. Very often, however, \(\mathcal{M}\) is subject to change because its development is iterative and its definition evolves through stages of incompleteness, where alternative design decisions are explored, typically to evaluate some quality trade-offs. Evolving systems specifications of this kind ask for novel verification approaches that tolerate incompleteness and support incremental analysis of alternative designs for certain functionalities. This is exactly the focus of this paper, which develops an incremental model-checking approach for evolving Statecharts. Statecharts have been chosen both because they are increasingly used in practice natively support model refinements.     

Admittance—Frequency Response in Zinc Oxide Varistor Ceramics

The lumped parameter/complex plane analysis technique revealed several contributions to the terminal admittance of the ZnO—Bi₂O₃ based varistor grain-boundary ac response. The terminal capacitance has been elucidated via the multiple trapping phenomena, a barrier layer polarization, and a resonance effect in the frequency range 10⁻²≤ f ≤ 10⁹ Hz. The characterization of the trapping relaxation behavior near ∼ 10⁵ Hz (∼ 10⁻⁶ s) provided a better understanding of a previously reported loss-peak. The possible nonuniformity in this trapping activity associated with its conductance term observed via the depression angle of a semicircular relaxation in the complex capacitance ( C *) plane has been postulated.     

Temperature-dependent diffusion coefficient of soluble substances during ethanol extraction of clove

The temperature dependence of the diffusion coefficient of ethanol-soluble substances from ground cloves (particle size 250 μm) during extraction was estimated by fitting batch extraction data at several temperatures (27.8, 40, 50, and 60°C) to a previously developed mass transfer model. The model was based on spherical geometry of particles. Nonlinear regression analysis was used to develop an equation that describes the diffusivity as a function of temperature. The temperature dependence ofD _A was of the Arrhenius type.     

An analytical framework for event mining in video data

With the high availability of digital video contents on the internet, users need more assistance to access digital videos. Various researches have been done about video summarization and semantic video analysis to help to satisfy these needs. These works are developing condensed versions of a full length video stream through the identification of the most important and pertinent content within the stream. Most of the existing works in these areas are mainly focused on event mining. Event mining from video streams improves the accessibility and reusability of large media collections, and it has been an active area of research with notable recent progress. Event mining includes a wide range of multimedia domains such as surveillance, meetings, broadcast, news, sports, documentary, and films, as well as personal and online media collections. Due to the variety and plenty of Event mining techniques, in this paper we suggest an analytical framework to classify event mining techniques and to evaluate them based on important functional measures. This framework could lead to empirical and technical comparison of event mining methods and development of more efficient structures at future.     

Synthesis and characterization of hydrophilic nanocomposite coating on glass substrate

Hydrophilic coatings based on 3‐glicidoxy propyl trimethoxy silane (GPTMS) and polyethylene glycol (PEG) were prepared with the incorporation of tetramethoxysilane (TMOS) and silica nanoparticle colloidal suspension by a sol–gel process. Characterization of the coatings has been performed by Fourier Transform Infrared (FTIR) and Attenuated Total Reflectance Infrared (ATR‐IR) techniques. Morphological properties were characterized by Scanning Electron Microscopy (SEM). The distribution of Si atoms in the hybrid system was obtained by Si mapping. The particle size in sol solution of the coating was measured by light scattering analyzer. Optical properties were characterized by using UV–vis spectrophotometer. The hydrophilicity of the coating was determined by contact angle measurements, and also the results have been confirmed by surface energy and water uptake investigations. The obtained results indicate that the surfactants affected the contact angles remarkably but did not change the transparency. It has been found that applying silica nano particles leads to coatings with different properties than those using TMOS, while siloxane contents were the same in these two set of coatings. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5322–5329, 2006     

A Possible Industrial Solution to Ferment Lignocellulosic Hydrolyzate to Ethanol: Continuous Cultivation with Flocculating Yeast

The cultivation of toxic lignocellulosic hydrolyzates has become a challenging research topic in recent decades. Although several cultivation methods have been proposed, numerous questions have arisen regarding their industrial applications. The current work deals with a solution to this problem which has a good potential application on an industrial scale. A toxic dilute-acid hydrolyzate was continuously cultivated using a high-cell-density flocculating yeast in a single and serial bioreactor which was equipped with a settler to recycle the cells back to the bioreactors. No prior detoxification was necessary to cultivate the hydrolyzates, as the flocks were able to detoxify it in situ. The experiments were successfully carried out at dilution rates up to 0.52 h⁻¹. The cell concentration inside the bioreactors was between 23 and 35 g-DW/L, while the concentration in the effluent of the settlers was 0.32 ± 0.05 g-DW/L. An ethanol yield of 0.42–0.46 g/g-consumed sugar was achieved, and the residual sugar concentration was less than 6% of the initial fermentable sugar (glucose, galactose and mannose) of 35.2 g/L.     

Performance evaluation of an importance sampling technique in a Jackson network

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.     

Centroid index: Cluster level similarity measure

In clustering algorithm, one of the main challenges is to solve the global allocation of the clusters instead of just local tuning of the partition borders. Despite this, all external cluster validity indexes calculate only point-level differences of two partitions without any direct information about how similar their cluster-level structures are. In this paper, we introduce a cluster level index called centroid index. The measure is intuitive, simple to implement, fast to compute and applicable in case of model mismatch as well. To a certain extent, we expect it to generalize other clustering models beyond the centroid-based k-means as well.