An anisotropic dressed pairwise potential model for the adsorption of noble gases on boron nitride sheets

Development of empirical potentials with accurate parameterization is indispensable while modeling large-scale systems. Herein, we report accurate parameterization of an anisotropic dressed pairwise potential model (PPM) for probing the adsorption...

Implicit multilinear modeling

The paper introduces a subclass of nonlinear differential-algebraic models of interest for applications. By restricting the nonlinearities to multilinear polynomials, it is possible to use modern tensor methods. This opens the door to new approximation and complexity reduction methods for large scale systems with relevant nonlinear behavior. The modeling procedures including composition, decomposition, normalization, and multilinearization steps are shown by an example of a local energy system with a nonlinear electrolyzer, a linear buck converter and a PI controller with saturation.

Interoperability in Internet of Media Things and Integration Big Media

Multimedia-related things is a new class of connected objects that can be searched, discovered, and composited on the internet of media things (IoMT). A huge amount of data sets come from audio-visual sources or have a multimedia nature. However, multimedia data is currently not incorporated in the big data (BD) frameworks. The research projects, standardization initiatives, and industrial activities for integration are outlined in this chapter. MPEG IoMT interoperability and network-based media processing (NBMP) framework as an instance of the big media (BM) reference model are explored. Conceptual model of IoT and big data integration for analytics is proposed. Big data analytics is rapidly evolving both in terms of functionality and the underlying model. The authors pointed out that IoMT analytics is closely related to big data analytics, which facilitates the integration of multimedia objects in big media applications in large-scale systems. These two technologies are mutually dependent and should be researched and developed jointly.

Reduction of linear dynamic systems using generalized approach of pole clustering method

A new model order abatement method based on the clustering of poles and zeros of a large-scale continuous time system is proposed. The clustering of poles and zeros are used for finding the cluster centres. The abated model is identified from the cluster centres, which reflect the effectiveness of the dominant poles of the clusters. The cluster centre is determined by taking [Formula: see text] root of the sum of the inverse of [Formula: see text] power of poles (zeros) in a particular cluster. It is famous that the magnitude of the pole cluster centre plays an important role in the clustering technique for the simplification of large-scale systems. The magnitude of the cluster centres computed by the modified pole clustering method or some other methods based on the pole clustering techniques is large as compared to the proposed technique. The less magnitude of pole cluster centre reflects the better approximations and proper matching of the abated model with the original system. Therefore, the proposed method offers better approximations matching between actual and abated systems during the transient period compared to some other clustering methods, which supports the replacement of large-scale systems by proposed abated systems. The proposed technique is a generalized version of the standard pole clustering technique. The proposed method guarantees the retention of dominant poles, stability and other fundamental control properties of the actual plant in the abated model. The proposed algorithm is illustrated by the five standard systems taken from the literature. The accuracy and effectiveness of the proposed method are verified by comparing the time responses and various performance error indices.

Induction and evaluation of secondary metabolite and antioxidant activity in adventitious root of Codonopsis javanica

In this study, the effects of auxin (IBA, NAA), explants, and culture conditions (light/dark) on adventitious root induction of Codonopsis javanica were investigated. The results showed that dark conditions were more suitable for adventitious root induction than light conditions. All three types of explants (internodes, leaves, and nodes) induced adventitious roots, and the appropriate concentration of auxin was 0.5 mg/l IBA. After 4 weeks of incubation under dark conditions, the rooting percentage and number of roots/explant of internode, leaf, and node segments on media supplemented with 0.5 mg/l IBA were 100% and 33.87 roots, 97.78% and 23.48 roots, 100% and 25.20 roots, respectively. These adventitious roots were analysed for the presence of alkaloids, carbohydrates, saponin, fixed oils and fats, phenol, flavonoids, gum, and mucilage. The total polysaccharide content, total phenolic content, and the antioxidant activity (IC50) of C. javanica adventitious root biomass were 16.98%, 1.876 (mg GAE/g DW), and 2.44 (mg/ml), respectively. These results indicate that the adventitious roots of C. javanica contain bioactive compounds, which can be used as a material source for multiplication in large-scale systems.

On stochastic Kaczmarz type methods for solving large scale systems of ill-posed equations

In this article we investigate a family of "stochastic gradient type methods", for solving systems of linear ill-posed equations. The method under consideration is a stochastic version of the projective Landweber-Kaczmarz (PLWK) method in [Leitão/Svaiter, Inv. Probl. 2016] (see also [Leitão/Svaiter, NFAO 2018]). In the case of exact data, mean square convergence to zero of the iteration error is proven. In the noise data case, we couple our method with an a priori stopping rule and characterize it as a regularization method for solving systems of linear ill-posed operator equations. Numerical tests are presented for two linear ill-posed problems: (i) a Hilbert matrix type system with over 10^8 equations; (ii) a Big Data linear regression problem with real data. The obtained results indicate superior performance of the proposed method when compared with other well established iterations. Our preliminary investigation indicates that the proposed iteration is a promising alternative for computing stable approximate solutions of large scale systems of linear ill-posed equations.