Decentralized fault detection and diagnosis via sparse PCA based decomposition and Maximum Entropy decision fusion

This paper proposes an approach for decentralized fault detection and diagnosis in process monitoring sensor networks. The sensor network is decomposed into multiple, potentially overlapping, blocks using the Sparse Principal Component Analysis algorithm. Local predictions are generated at each block using Support Vector Machine classifiers. The local predictions are then fused via a Maximum Entropy algorithm. Empirical studies on the benchmark Tennessee Eastman Process data demonstrated that the proposed decentralized approach achieves accuracy comparable to that of the fully centralized approach, while offering benefits in terms of fault tolerance, reusability, and scalability.     

Supervised clustering of label ranking data using label preference information

This paper studies supervised clustering in the context of label ranking data. The goal is to partition the feature space into K clusters, such that they are compact in both the feature and label ranking space. This type of clustering has many potential applications. For example, in target marketing we might want to come up with K different offers or marketing strategies for our target audience. Thus, we aim at clustering the customers’ feature space into K clusters by leveraging the revealed or stated, potentially incomplete customer preferences over products, such that the preferences of customers within one cluster are more similar to each other than to those of customers in other clusters. We establish several baseline algorithms and propose two principled algorithms for supervised clustering. In the first baseline, the clusters are created in an unsupervised manner, followed by assigning a representative label ranking to each cluster. In the second baseline, the label ranking space is clustered first, followed by partitioning the feature space based on the central rankings. In the third baseline, clustering is applied on a new feature space consisting of both features and label rankings, followed by mapping back to the original feature and ranking space. The RankTree principled approach is based on a Ranking Tree algorithm previously proposed for label ranking prediction. Our modification starts with K random label rankings and iteratively splits the feature space to minimize the ranking loss, followed by re-calculation of the K rankings based on cluster assignments. The MM-PL approach is a multi-prototype supervised clustering algorithm based on the Plackett-Luce (PL) probabilistic ranking model. It represents each cluster with a union of Voronoi cells that are defined by a set of prototypes, and assign each cluster with a set of PL label scores that determine the cluster central ranking. Cluster membership and ranking prediction for a new instance are determined by cluster membership of its nearest prototype. The unknown cluster PL parameters and prototype positions are learned by minimizing the ranking loss, based on two variants of the expectation-maximization algorithm. Evaluation of the proposed algorithms was conducted on synthetic and real-life label ranking data by considering several measures of cluster goodness: (1) cluster compactness in feature space, (2) cluster compactness in label ranking space and (3) label ranking prediction loss. Experimental results demonstrate that the proposed MM-PL and RankTree models are superior to the baseline models. Further, MM-PL is has shown to be much better than other algorithms at handling situations with significant fraction of missing label preferences.     

Identification of Secretory Compounds from the European Callipodidan Species <Emphasis Type="Italic">Apfelbeckia insculpta</Emphasis>

Defensive secretions of the callipodidan species Apfelbeckia insculpta contain a p-cresol as the main component and phenol in traces. This is the first identification of these compounds in a European callipodidan species. The repugnatory glands of A. insculpta are of the spirobolid type and consist of a spherical reservoir, a simple duct, and a valvular cuticular infolding that opens onto the lateral surface of the millipede via a pore.     

Characterizing the structure of pharmaceutical granules obtained by wet granulation with varying amounts of water via Raman chemical imaging

A pharmaceutical formulation containing metformin hydrochloride (MET), hydroxypropyl cellulose (HPC), and microcrystalline cellulose (MCC) was wet granulated with varying amounts of water and the structure of the obtained granules was characterized by Raman chemical mapping. Univariate Raman mapping was found to be satisfactory for producing the images of the two components of interest (HPC and MCC). In addition to the images, the average Raman spectra from the maps as well as the micro-Raman spectra from the hot pixels were analyzed. HPC is found to strongly respond to the addition of water, with its domain dissipating and Raman bands becoming weaker as the water addition increases. MCC is also responsive to water, reacting similarly to HPC but to a much smaller extent and only for the largest amounts of water. Granules made with increasing water content also have improved tabletting properties and flow.     

Study of multicycle melting and freezing of sodium thiosulphate pentahydrate

The behaviour of sodium thiosulphate pentahydrate in the course of repeated use as a heat-storing medium can be predicted, cycle by cycle, on the basis of a generalised phase-transition equation adapted for incongruently melting material. An indice is derived for this purpose and named ‘coefficient of true phase-transition reversibility’. Its predictive value is shown for three additional incongruently melting materials well known as heat-storing media: CaCl₂.6H₂O, Na₂SO₄.10H₂O and the mixture Na₂SO₄.10H₂O + 2/3NH₄Cl + 2/3NaCJ.     

Torque calculation between circular coils with inclined axes in air

In this paper we derive new semi‐analytical expressions for calculating the electromagnetic torque between inclined circular coils in air. The torque calculation has been obtained from the corresponding mutual inductance between inclined circular coils using the filament method. The coils of rectangular cross‐section whose centers are at the same and the different axes have been considered. From this general case it is possible to calculate the torque between all possible coil combinations either with rectangular or neglected cross‐section. Results obtained by the presented approach are in very good agreement with already published data. This method can be used for industrial electromagnetic devices such as torque sensors, transducers and torque‐measuring devices. Copyright © 2010 John Wiley & Sons, Ltd.     

Substituted imino and amino derivatives of 4-hydroxycoumarins as novel antioxidant,antibacterial and antifungal agents: Synthesis and in vitro assessments

A series of imino and amino derivatives of 4-hydroxycoumarins were synthesised and evaluated for antioxidant potential, through different in vitro models such as (DPPH) free radical-scavenging activity, linoleic acid emulsion model system, reducing power assay and phosphomolybdenum method. Also, antimicrobial activity of obtained coumarins was evaluated against 13 bacteria and eight fungi. All prepared compounds possessed good antioxidant activity and among them a p-nitrophenol derivative with IC₅₀ at 25.9 μM possessed radical-scavenging activity which was comparable to BHT. Observed data for antibacterial activity indicated strong activity of all tested amino derivatives, while imines showed better antifungal properties.