The medicine recommendation system is intended to suggest alternative medicines based on the cosine similarity between a patient's symptoms and the effects of various medications. The system makes use of a database of medications and their indications, as well as a list of symptoms that a patient may exhibit. It vectorizes the data, applies filters, and makes suggestions. Medicines with a higher cosine similarity are considered more relevant and recommended to patients. In the scenario of a medical emergency, when physicians or prescribed medications are unavailable, this recommender serves as a valuable resource. The proposed medicine recommendation system has the potential to help healthcare professionals and patients make educated decisions about alternative medications. The system can reduce the risk of adverse drug reactions and improve patient outcomes by suggesting alternative medicines that are more effective and have fewer side effects. Overall, the proposed medicine recommendation system has the potential to significantly improve patient care by making effective recommendations for alternative medications. It can also reduce healthcare professionals’ workload by automating the process of identifying.

Due to the intrinsic properties of transactional data, like concept drift, noise, data imbalance, and borderline entities, the fraud detection poses a challenging issue in bank transaction. A number of solutions are developed for detecting the fraud, but these solutions reveal ineffective performance. Therefore, an effective fraud detection framework named Harris Grey Wolf (HGW)-based Deep stacked auto encoder is proposed to perform the fraud detection mechanism in bank transaction by solving the data imbalance issues. The HGW-based deep stacked auto encoder is developed using the characteristic features of the standard Harris Hawks Optimizer (HHO), and Grey Wolf Optimizer (GWO). The proposed HGW-based Deep stacked auto encoder provides an effective and optimal solution in detecting the frauds using the fitness function, which considers the minimal error value and evaluate the best solution based on the iterations. The useful and the appropriate features are effectively selected from the transactional data, as these features enhanced the accuracy of detection rate.

This paper, the efficient and effective fraud detection technique, termed SpiHWO-based Deep RNNtechnique is developed. At first, the data transformation is performed for transforming the data using Yeo-Johnson transformation. After that, the effective features are selected based on wrapper method where the best features are selected for further processing. Then, by using selected features, fraud detection is executed based on Deep RNN classifier, which is trained by developed SpiHWO technique. The proposed SpiHWO algorithm is newly developed by combining the SMO algorithm and HWO algorithm. Furthermore, the performance of developed method is computed using performance metrics, like sensitivity, specificity and also accuracy. The developed method achieved improved performance with respect to accuracy of 0.951, sensitivity of 0.985 and specificity of 0.792.

Purpose Fraud transaction detection has become a significant factor in the communication technologies and electronic commerce systems, as it affects the usage of electronic payment. Even though, various fraud detection methods are developed, enhancing the performance of electronic payment by detecting the fraudsters results in a great challenge in the bank transaction. Design/methodology/approach This paper aims to design the fraud detection mechanism using the proposed Harris water optimization-based deep recurrent neural network (HWO-based deep RNN). The proposed fraud detection strategy includes three different phases, namely, pre-processing, feature selection and fraud detection. Initially, the input transactional data is subjected to the pre-processing phase, where the data is pre-processed using the Box-Cox transformation to remove the redundant and noise values from data. The pre-processed data is passed to the feature selection phase, where the essential and the suitable features are selected using the wrapper model. The selected feature makes the classifier to perform better detection performance. Finally, the selected features are fed to the detection phase, where the deep recurrent neural network classifier is used to achieve the fraud detection process such that the training process of the classifier is done by the proposed Harris water optimization algorithm, which is the integration of water wave optimization and Harris hawks optimization. Findings Moreover, the proposed HWO-based deep RNN obtained better performance in terms of the metrics, such as accuracy, sensitivity and specificity with the values of 0.9192, 0.7642 and 0.9943. Originality/value An effective fraud detection method named HWO-based deep RNN is designed to detect the frauds in the bank transaction. The optimal features selected using the wrapper model enable the classifier to find fraudulent activities more efficiently. However, the accurate detection result is evaluated through the optimization model based on the fitness measure such that the function with the minimal error value is declared as the best solution, as it yields better detection results.

A semi-organic nonlinear optical material phosphoric acid pyridine-1-ium-2-carboxylate (PAPC) crystal has been synthesized and grown. Vibrational spectral analysis and NMR spectral analysis has been carried out. Mechanical studies on the grown crystal has been performed which disclose the material belongs to soft materials category. The thermal behaviour of the grown crystal has been investigated by thermogravimetric and differential thermal analysis. UV–Visible spectral analysis has been carried out which reveals that the grown crystal is transparent in the entire visible region with the lower cut-off wavelength of 298 nm and the derived optical constant attests the suitability of this material for non-linear optical applications. The third order nonlinearity has been studied by z-scan method and the enhanced third-order nonlinearity shows PAPC is a potential material for device applications. Second harmonic generation efficiency has been studied by Kurtz and Perry powder test and is found as 0.14 times greater than the KDP.

In this study, single crystals of urea ninhydrin monohydrate (UNMH) have been grown by slow evaporation method. The grown crystals were characterized by FT-IR, FT-Raman and UV-Vis-NIR spectroscopies. The Kurtz and Perry powder method was employed to confirm the near-zero SHG efficiency of the as-grown centrosymmetric UNMH crystal. The third order nonlinearity of the crystal has been studied by the open aperture Z-scan method. The nonlinear absorption coefficient is calculated and the potentiality of UNMH in optical limiting applications is identified. The molecular geometry and the origin of optical non-linearity at the molecular level have been investigated by the density functional theory. The normal coordinate analysis was carried out to assign the molecular vibrational modes. Vibrational spectral studies confirms the presence of weak O-H⋯O and moderate O-H⋯O type hydrogen bonds in the molecule as well as O-H⋯O, N-H⋯O and blue-shifted C-H⋯O type H-bonds in the crystal. The intramolecular charge transfer interactions and the electronic absorption mechanisms have been discussed. The static and the dynamic values of hyperpolarizabilities for UNMH were estimated theoretically by DFT methods.

Crystals of guanidinium oxalate monohydrate (GUOM), a salt of a functional guanidine derivative, crystallising with the space group of P2 1 /c, is synthesised and characterised by single-crystal XRD, NMR, UV-Vis and vibrational spectroscopy.The assignment of spectral bands is carried out in terms of the fundamental modes of vibration of the guanidinium cation and oxalate anion.Thermal analysis (TG/DTA) indicates that the compound is thermally robust.GUOM also exhibits antimicrobial activity against a few microorganisms.

With the growing demand of medical data processing and predictive analysis, finding the frequent itemset and association rules are becoming the major focus of the research. The association rule based analysis helps the researchers and analysts to identify the relations and dependencies between various parameters in the dataset. This knowledge can be useful in identifying the cause of the disease for the patient. Voluminous amount of researches are been conducted in order to establish the best association rule mining algorithm similar to Apriori algorithm. Nevertheless, the improvements can be demonstrated. Hence, this work proposes an Apriori association rule discovery based technique and demonstrate the improvements over the existing research methods. Another significant outcome of this work is to establish the relationships between the healthcare parameters with the heart disease symptoms. The work is targeted to improve the precaution measures for the patients in order to save the precious human life.

The FTIR and UV spectroscopic analysis have been carried out on guanidinium phthalate (GUP) crystal, an organic nonlinear optical material. The spectra are interpreted with the aid of normal coordinate analysis following structure optimizations and force field calculations based on density functional theory (DFT). The thermogravimetric (TG) and differential thermal analysis (DTA) ensures the thermal stability of the compound. Vickers microhardness values reveals the mechanical strength of the crystal.

A new organic nonlinear optical hydrogen bonding complex salt of 3-carboxyl anilinium p-toluene sulfonate has been synthesized and highly transparent good quality single crystals of it were successfully grown employing slow solvent evaporation solution growth technique at ambient temperature. The (1)H and (13)C NMR spectra were recorded to establish the molecular structure. The single crystal XRD analysis carried out reveals that the title salt crystallizes in monoclinic crystal system with non-centrosymmetric P2₁ space group. The FT-IR spectrum was recorded to confirm the presence of various functional groups in the grown title crystal. The UV-Vis-NIR transmission spectrum was recorded to apprehend the suitability of the single crystal of the title salt for various optical and NLO applications. The TG/DTA thermal analysis was performed to establish the thermal stability of the crystal. The SHG activity in the grown crystal was identified employing the modified Kurtz-Perry powder test. The electronic charge distribution and reactivity of the molecules within the title complex was studied by HOMO and LUMO analysis and the molecular electrostatic potential (MEP) of the title crystal was performed using the B3LYP method.

Bis (glycinium) oxalate, an organic nonlinear optical material, has been synthesized and single crystals, with dimensions up to22x6x5 mm3, have been grown from aqueous solution. The crystal belongs to the centro symmetric space group P21/c. The structural perfection of the grown crystals has been analysed by high-resolution X-ray diffraction (HRXRD) rocking curve measurements. Fourier transform infrared (FTIR) spectroscopic studies were also performed for the identification of different modes present in the compound. The UV–vis transmission spectrum has been recorded in the range 200–1000 nm. Thermal behaviour was studied by TG and DTA. The Vicker’s microhardness values were measured for the grown crystal.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

The protein superfamily classification problem, which consists of determining the superfamily membership of a given unknown protein sequence, is very important for a biologist for many practical reasons, such as drug discovery, prediction of molecular function and medical diagnosis. In this work, we propose a new approach for protein classification based on a Probabilistic Neural Network and feature selection. Our goal is to predict the functional family of novel protein sequences based on the features extracted from the protein's primary structure i.e., sequence only. For this purpose, the datasets are extracted form Protein Data Bank(PDB), a curated protein family database, are used as training datasets. In these conducted experiments, the performance of the classifier is compared to other known data mining approaches / sequence comparison methods. The computational results have shown that the proposed method performs better than the other ones and looks promising for problems with characteristics similar to the problem.

Single crystals of 2-carboxypyridinium hydrogen (2R,3R)-tartrate monohydrate, an organic nonlinear optical material has been grown by slow solvent evaporation technique. The single crystal X-ray diffraction (XRD) data revealed the noncentrosymmetric crystal structure, which is an essential criterion for second harmonic generation. The crystalline nature of the grown crystals was confirmed using powder XRD technique. The functional group of the compound is identified by FTIR spectrum. The thermal stability has been identified for the new title compound. The UV–vis spectrum shows the lower optical cut off at 300nm and transparent in the visible region. The second harmonic generation efficiency was found using Kurtz powder technique. The mechanical properties of the grown crystals have been studied using Vickers microhardness tester.

The bulk single crystal of 2-picolinic acid hydrochloride (PHCL) (a semi-organic nonlinear optical material of dimensions 25 x 15 x 10 mm(3)) was successfully grown by slow solvent evaporation technique. The XRD results revealed the cell parameters and the centrosymmetric nature of the crystal structure. FT-IR spectral study identified the functional groups, nature of bonding and their bond strength. The UV-Vis-NIR studies recognized the optical transmittance window and the lower cut off wavelength of the PHCL crystal and thus it could be performed as a NLO material. 1H NMR and (CNMR)-C-13 spectra were correlated with the XRD standard for the molecular structure reveals harmony of the materials. Thermal properties of the crystal were studied by thermo gravimetric analysis (TGA) and differential thermal analysis (DTA); the derived kinetic parameter values support the intuitive association of picolinicacid and HCI leads to the spontaneous formation of PHCL with a first order reaction. The presence of a proton and a proton acceptor groups provide the necessary stability to induce charge asymmetry in the PHCL structure. The load dependent hardness values of the crystal were measured by microhardness testing. (C) 2013 Elsevier B.V. All rights reserved.

A new charge transfer molecular complex salt of picric acid with m-toluidine was synthesized and the structure confirmed by single crystal X-ray diffraction (XRD) and NMR spectral analyses. Single crystals of m-toluidinium picrate have been grown by slow solvent evaporation solution growth technique using ethanol as the solvent at ambient temperature. The single crystal XRD analysis of MTP salt confirms the formation of 1:1 charge transfer salt in which the constituent ions are held together by strong intermolecular N-H-O type hydrogen bonds. The title compound crystallizes in monoclinic crystal system with centrosymmetric space group P21/c. The optical properties were studied by the UV-Vis-NIR transmittance and the fluorescence emission studies. Fourier transform infrared (FT IR) spectral analysis was used to confirm the presence of various functional groups in the grown crystal. Thermal stability of the grown MTP crystal was established using the thermo gravimetric and differential thermal analysis.

A new organic charge transfer molecular complex salt of o-toluidinium picrate (OTP) was synthesised and the single crystals were grown by the slow solvent evaporation solution growth technique using methanol as a solvent at room temperature. Formation of the new crystal has been confirmed by single crystal X-ray diffraction (XRD) and NMR spectroscopic techniques. The crystal structure determined by single crystal X-ray diffraction indicates that both the cation and the anion are interlinked to each other by three types of intermolecular hydrogen bonds, namely N(4)-H(4A)···O(7), N(4)-H(4B)···O(5) and N(4)-H(4C)···O(7). The title compound (OTP) crystallizes in monoclinic crystal system with the centrosymmetric space group P21/c. Fourier transform infrared (FT IR) spectral analysis was used to confirm the presence of various functional groups in the grown crystal. The optical properties were analyzed by the UV-Vis-NIR and fluorescence emission studies.

FT-IR, FT-Raman and UV-Vis spectra of the nonlinear optical molecule ninhydrin have been recorded and analyzed. The equilibrium geometry, bonding features, and harmonic vibrational wavenumbers have been investigated with the help of B3LYP density functional theory method. A detailed interpretation of the vibrational spectra is carried out with the aid of normal coordinate analysis following the scaled quantum mechanical force field methodology. Solvent effects have been calculated using time-dependent density functional theory in combination with the polarized continuum model. Natural bond orbital analysis confirms the occurrence of strong intermolecular hydrogen bonding in the molecule. Employing the open-aperture z-scan technique, nonlinear optical absorption of the sample has been studied in the ultrafast and short-pulse excitation regimes, using 100 fs and 5 ns laser pulses respectively. It is found that ninhydrin exhibits optical limiting for both excitations, indicating potential photonic applications.