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Graph theoretical molecular descriptors alias topological indices are a convenient means for expressing in numerical form the chemical structure encoded in a molecular graph. The structure descriptors derived from molecular graphs are widely used in quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies. The reason for introducing new indices is to obtain predictions of target properties of considered molecules that are better than the predictions obtained using already known indices. In this paper, we apply the reduced reverse degree based indices introduced in 2021 by Vignesh et al. In the QSPR analysis, we first compute the reduced reverse degree based indices for a family of benzenoid hydrocarbon molecules and then we obtain the correlation with the Physico-chemical properties of the considered molecules. We show that all the properties taken into consideration for the benzenoid hydrocarbons can be very effectively predicted by the reduced reverse degree based indices. Also, we have compared the predictive capability of reduced reverse degree based topological descriptors against 16 existing degree based indices. Further, we compute the defined reduced reverse degree based topological indices for Hyaluronic Acid-Paclitaxel Conjugates $$(HAP)_{n}$$ ( H A P ) n , $$n \ge 1$$ n ≥ 1 .

In this paper, we employed Naïve Bayes, Markov blanket and Tabu search to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes are treated as criteria, to classify web services. From the experiments, we conclude that Naïve based Bayesian network performs better than other two techniques comparable to the classification done in literature.

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The memristor, the fourth fundamental elements have shown the potential to revolutionize the present storage, analog, and digital computational technologies. The ability to remember its previous state in the absence of any stimuli has made the memristor as a prime candidate for nonvolatile memory. However, the sneak path is one of the main problems hampering the implementation of memristor‐based crossbar memories. In this article, we introduce a new crossbar architecture that is capable of storing multibit per cell and eliminates the sneak paths without adding any complex circuitry. The approximate write delay of the proposed memory cell is 20 mS which is very close to the delay of the single bit cell. The proposed architecture was validated by storing four different logic states in each cell of the 4 × 4 memory. Hence, one memory cell of the proposed architecture replaces four cells of the single‐bit memory at the cost of one additional diode per cell. Therefore, the proposed scheme saves considerable area when compared with the conventional single‐bit memory array. The write/read operations are validated by a generic, accurate, and efficient “voltage threshold adaptive memristor” (VTEAM) model. The simulation results prove that the proposed circuitry can read the memory content even after 2000 cycles without any sneak paths problem.