Exact Knowledge Hiding through Database Extension

In this paper, we propose a novel, exact border-based approach that provides an optimal solution for the hiding of sensitive frequent itemsets by (i) minimally extending the original database by a synthetically generated database part - the database extension, (ii) formulating the creation of the database extension as a constraint satisfaction problem, (iii) mapping the constraint satisfaction problem to an equivalent binary integer programming problem, (iv) exploiting underutilized synthetic transactions to proportionally increase the support of non-sensitive itemsets, (v) minimally relaxing the constraint satisfaction problem to provide an approximate solution close to the optimal one when an ideal solution does not exist, and (vi) by using a partitioning in the universe of the items to increase the efficiency of the proposed hiding algorithm. Extending the original database for sensitive itemset hiding is proved to provide optimal solutions to an extended set of hiding problems compared to previous approaches and to provide solutions of higher quality. Moreover, the application of binary integer programming enables the simultaneous hiding of the sensitive itemsets and thus allows for the identification of globally optimal solutions.     

Monolithic Perovskite/Silicon Tandems with >28% Efficiency: Role of Silicon-Surface Texture on Perovskite Properties

Textured silicon wafers used in silicon solar cell manufacturing offer superior light trapping, which is a critical enabler for high-performance photovoltaics. A similar optical benefit can be obtained in monolithic perovskite/silicon tandem solar cells, enhancing the current output of the silicon bottom cell. Yet, such complex silicon surfaces may affect the structural and optoelectronic properties of the overlying perovskite films. Here, through extensive characterization based on optical and microstructural spectroscopy, it is found that the main effect of such substrate morphology lies in an altering of the photoluminescence response of the perovskite, which is associated with thickness variations of the perovskite, rather than lattice strain or compositional changes. With this understanding, the design of high-performance perovskite/silicon tandems is rationalized, yielding certified power conversion efficiencies of >28%.     

Effective and efficient classification on a search-engine model

Traditional document classification frameworks, which apply the learned classifier to each document in a corpus one by one, are infeasible for extremely large document corpora, like the Web or large corporate intranets. We consider the classification problem on a corpus that has been processed primarily for the purpose of searching, and thus our access to documents is solely through the inverted index of a large scale search engine. Our main goal is to build the “best” short query that characterizes a document class using operators normally available within search engines. We show that surprisingly good classification accuracy can be achieved on average over multiple classes by queries with as few as 10 terms. As part of our study, we enhance some of the feature-selection techniques that are found in the literature by forcing the inclusion of terms that are negatively correlated with the target class and by making use of term correlations; we show that both of those techniques can offer significant advantages. Moreover, we show that optimizing the efficiency of query execution by careful selection of terms can further reduce the query costs. More precisely, we show that on our set-up the best 10-term query can achieve 93% of the accuracy of the best SVM classifier (14,000 terms), and if we are willing to tolerate a reduction to 89% of the best SVM, we can build a 10-term query that can be executed more than twice as fast as the best 10-term query.     

Optimizing the coagulation process in a drinking water treatment plant -- comparison between traditional and statistical experimental design jar tests

In this study of coagulation operation, a comparison was made between the optimum jar test values for pH, coagulant and coagulant aid obtained from traditional methods (an adjusted one-factor-at-a-time (OFAT) method) and with central composite design (the standard design of response surface methodology (RSM)). Alum (coagulant) and polymer (coagulant aid) were used to treat a water source with very low pH and high aluminium concentration at Sri-Gading water treatment plant (WTP) Malaysia. The optimum conditions for these factors were chosen when the final turbidity, pH after coagulation and residual aluminium were within 0-5 NTU, 6.5-7.5 and 0-0.20 mg/l respectively. Traditional and RSM jar tests were conducted to find their respective optimum coagulation conditions. It was observed that the optimum dose for alum obtained through the traditional method was 12 mg/l, while the value for polymer was set constant at 0.020 mg/l. Through RSM optimization, the optimum dose for alum was 7 mg/l and for polymer was 0.004 mg/l. Optimum pH for the coagulation operation obtained through traditional methods and RSM was 7.6. The final turbidity, pH after coagulation and residual aluminium recorded were all within acceptable limits. The RSM method was demonstrated to be an appropriate approach for the optimization and was validated by a further test.     

Rough-Set-based timing characteristic analyses of distance protective relay

Nowadays protection engineers are suffering from very complex implementations of protection system analysis due to massive quantities of inconsistent data, let alone coming from diverse intelligent electronic devices (IEDs). Thus, a novel Rough-Set-based data mining strategy has been formulated to resolve the inconsistency in a distance protective relay's decision system (i.e. a transformed relay event report) in such a way that the relay's timing characteristics hidden in its decision algorithm of protection operations have been successfully discovered. Using Rough Set Theory, the inherent uncertainty and vagueness in the relay event report have been resolved using the concepts of discernibility, elementary sets and set approximations. The timing characteristics that have been successfully discovered are in relation to the relay trip assertion activity, impedance element activation, fault characteristics, circuit breaker operation and its overall decision system approximation.     

Silver Nanoparticles from Oregano Leaves’ Extracts as Antimicrobial Components for Non-Infected Hydrogel Contact Lenses

The oregano leaves’ extract (ORLE) was used for the formation of silver nanoparticles (AgNPs(ORLE)). ORLE and AgNPs(ORLE) (2 mg/mL) were dispersed in polymer hydrogels to give the pHEMA@ORLE_2 and pHEMA@AgNPs(ORLE)_2 using hydroxyethyl–methacrylate (HEMA). The materials were characterized by X-ray fluorescence (XRF) spectroscopy, X-ray powder diffraction analysis (XRPD), thermogravimetric differential thermal analysis (TG-DTA), derivative thermogravimetry/differential scanning calorimetry (DTG/DSC), ultraviolet (UV-Vis), and attenuated total reflection mode (ATR-FTIR) spectroscopies in solid state and UV–Vis in solution. The crystallite size value, analyzed with XRPD, was determined at 20 nm. The antimicrobial activity of the materials was investigated against Gram-negative bacterial strains Pseudomonas aeruginosa (P. aeruginosa) and Escherichia coli (E. coli). The Gram-positive ones of the genus of Staphylococcus epidermidis (S. epidermidis) and Staphylococcus aureus (S. aureus) are known to be involved in microbial keratitis by the means of inhibitory zone (IZ), minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC). The IZs, which developed upon incubation of P. aeruginosa, E. coli, S. epidermidis, and S. aureus with paper discs soaked in 2 mg/mL of AgNPs(ORLE), were 11.7 ± 0.7, 13.5 ± 1.9, 12.7 ± 1.7, and 14.3 ± 1.7 mm. When the same dose of ORLE was administrated, the IZs were 10.2 ± 0.7, 9.2 ± 0.5, 9.0 ± 0.0, and 9.0 ± 0.0 mm. The percent of bacterial viability when they were incubated over the polymeric hydrogel discs of pHEMA@AgNPs(ORLE)_2 was interestingly low (66.5, 88.3, 77.7, and 59.6%, respectively, against of P. aeruginosa, E. coli, S. epidermidis, and S. aureus) and those of pHEMA@ORLE_2 were 89.3, 88.1, 92.8, and 84.6%, respectively. Consequently, pHEMA@AgNPs(ORLE)_2 could be an efficient candidate toward the development of non-infectious contact lenses.     

Emulsion stability of clove oil in chitosan and sodium alginate matrix

Clove oil was emulsified in 1% w/w chitosan (CC emulsions) and 2.5% w/w sodium alginate matrix (CA emulsions) containing Tween 80 as the surfactant. Different homogenization speeds (5,000, 10,000, 15,000 and 20,000 rpm) were used to produce the emulsions, and the stability of the emulsions during storage (29 days) was determined. The stability of the emulsions containing clove oil prior to the solidification process was assessed when chitosan and sodium alginate were used as encapsulating materials. Different homogenization speeds resulted in polydisperse emulsions with a size of 2–3 μm and 90% of stability after 29 days of storage. Different homogenization speeds did not significantly affect the concentrations of the active compounds contained in the emulsions. However, these concentrations changed significantly after 29 days of storage when sodium alginate was used to make the emulsions and the homogenization speeds were ≥ 10,000 rpm. High temperature caused by the high viscosity of the solution and high energy dissipation during homogenization suggested that the emulsions composed of sodium alginate were unstable. Chitosan enabled a longer processing time during the clove oil encapsulation process compared to sodium alginate, when emulsification by homogenization was used. The stability of the emulsion of the clove oil-in-chitosan matrix prior to the solidification step was superior.     

Correspondence mapping induced state and action metrics for robotic imitation.

This paper addresses the problem of body mapping in robotic imitation where the demonstrator and imitator may not share the same embodiment [degrees of freedom (DOFs), body morphology, constraints, affordances, and so on]. Body mappings are formalized using a unified (linear) approach via correspondence matrices, which allow one to capture partial, mirror symmetric, one-to-one, one-to-many, many-to-one, and many-to-many associations between various DOFs across dissimilar embodiments. We show how metrics for matching state and action aspects of behavior can be mathematically determined by such correspondence mappings, which may serve to guide a robotic imitator. The approach is illustrated and validated in a number of simulated 3-D robotic examples, using agents described by simple kinematic models and different types of correspondence mappings.