A privacy-preserving model based on differential approach for sensitive data in cloud environment

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully trust this environment. However, it has become a challenge to ensure privacy preservation when sharing data effectively among different parties. This paper proposes a novel model that partitions data into sensitive and non-sensitive parts, injects the noise into sensitive data, and performs classification tasks using k-anonymization, differential privacy, and machine learning approaches. It allows multiple owners to share their data in the cloud environment for various purposes. The model specifies communication protocol among involved multiple untrusted parties to process owners’ data. The proposed model preserves actual data by providing a robust mechanism. The experiments are performed over Heart Disease, Arrhythmia, Hepatitis, Indian-liver-patient, and Framingham datasets for Support Vector Machine, K-Nearest Neighbor, Random Forest, Naive Bayes, and Artificial Neural Network classifiers to compute the efficiency in terms of accuracy, precision, recall, and F1-score of the proposed model. The achieved results provide high accuracy, precision, recall, and F1-score up to 93.75%, 94.11%, 100%, and 87.99% and improvement up to 16%, 29%, 12%, and 11%, respectively, compared to previous works.

     

Design aspects of MOS-controlled thyristor elements: technology,simulation, and experimental results

2.5-kV thyristor devices have been fabricated with integrated MOS controlled n⁺-emitter shorts and a bipolar turn-on gate using a p-channel DMOS technology. Square-cell geometries with pitch variations ranging from 15 to 30 μm were implemented in one- and two-dimensional arrays with up to 20000 units. The impact of the cell pitch on the turn-off performance and the on-state voltage was studied for arrays with constant cathode area as well as for single-cell structures. By realizing MOS components with submicrometer channel lengths, scaled single cells are shown to turn off with current densities of several kiloamperes per square centimeter at a gate bias of 5 V. In the case of multi-cell ensembles, turn-off performance is limited due to inhomogeneous current distribution. Critical process parameters as well as the device behavior were optimized through multidimensional numerical simulation     

Hybrid numerical scheme for time-evolving wave fields

Many problems in geophysics, acoustics, elasticity theory, cancer treatment, food process control and electrodynamics involve study of wave field synthesis (WFS) in some form or another. In the present work, modelling of wave propagation phenomena is studied as a static problem, using finite element method and treating time as an additional spatial dimension. In particular, WFS problems are analysed using discrete methods. It is shown that a fully finite element-based scheme is very natural and effective method for the solution of such problems. Distributed WFS in the context of two-dimensional problems is outlined and incorporation of any geometric or material non-linearities is shown to be straightforward. This has significant implications for problems in geophysics or biological media, where material inhomogeneities are quite prevalent. Numerical results are presented for several problems referring to media with material inhomogeneities and predefined absorption profiles. The method can be extended to three-dimensional problems involving anisotropic media properties in a relatively straightforward manner. Copyright © 2006 John Wiley & Sons, Ltd.     

Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Attrition of spherical electrode carbon particles during batch fluidized combustion

Spherical electrode carbon particles prepared from carbon rods of dry cell batteries have been used to study the attrition behaviour in a bubbling fluidized bed combustor. Experiments have been conducted in a 40 mm I.D. and 1 m high fluidized bed combustor operated at 1 m/s superficial velocity. The bed was operated with nitrogen and with two different oxygen concentrations at 850°C to study the effect of combustion on attrition of these particles. The experimental technique used allowed the time resolution of attrited fines generation, providing detailed curves of attrition rates as a function of time. Attrition rate constants have been evaluated. Results show an enhancement of attrition due to combustion even for spherical, homogeneous and smooth particles.     

Combustion of single char particles in a turbulent fluidized bed

The combustion of single bituminous char particles (4-12 mm diameter) was studied in a turbulent fluidized bed operated at 1098 K using air as the fluidising medium. Results indicated that particles burn with constant density following a shrinking sphere model. Burning rates are much higher than those observed in a bubbling fluidized bed. The rate of transfer of oxygen to the particle surface is also higher than that observed in bubbling beds. A model is proposed to calculate the Sherwood numbers of the burning carbon particles. Experimental values of the Sherwood numbers agree well with those predicted from the model.     

Structural drivers controlling sulfur solubility in alkali aluminoborosilicate glasses

If the direct feed approach to vitrify the Hanford's tank waste is implemented, the low activity waste (LAW) will comprise higher concentrations of alkali/alkaline-earth sulfates than expected under the previously proposed vitrification scheme. To ensure a minimal impact of higher sulfate concentrations on the downstream operations and overall cost of vitrification, advanced glass formulations with enhanced sulfate loadings (solubility) are needed. While, the current sulfate solubility predictive models have been successful in designing LAW glasses with sulfate loadings <2 wt.%, it will be difficult for them to design glass compositions with enhanced loadings due to our limited understanding of the fundamental science governing these processes. In this pursuit, this article unearths the underlying compositional and structural drivers controlling the sulfate solubility in model LAW glasses. It has been shown that the preferentially removes non-framework cations from the modifier sites in the silicate network, thus, leading to the polymerization in the glass network via the formation of ring-structured borosilicate units. Furthermore, though the sulfate solubility slightly decreases with increasing Li⁺/Na⁺ in the glasses, the prefers to be charge compensated by Na⁺, as it is easier for to break Na–O bonds instead of Li–O bonds.     

Long-wave interfacial instabilities in a thin electrolyte film undergoing coupled electrokinetic flows: a nonlinear analysis

Spatiotemporal deformations of the free charged surface of a thin electrolyte film undergoing a coupled electrokinetic flow composed of an electroosmotic flow (EOF) on a charged solid substrate and an electrophoretic flow (EPF) at its free surface are explored through linear stability analysis and the long-wave nonlinear simulations. The nonlinear evolution equation for the deforming surface is derived by considering both the Maxwell’s stresses and the hydrodynamic stresses. The electric potential across the film is obtained from the Poisson–Boltzmann equation under the Debye–Hückel approximation. The simulations show that at the charged electrolyte–air interface, the applied electric field generates an EPF similar to that of a large charged particle. The EOF near the solid–electrolyte interface and the EPF at the electrolyte–air interface are in the same (or opposite) directions when the zeta potentials at the two interfaces are of the opposite (or same) signs. The linear and nonlinear analyses of the evolution equation predict the presence of travelling waves, which is strongly modulated by the applied electric field and the magnitude/sign of the interface zeta potentials. The time and length scales of the unstable modes reduce as the sign of zeta potential at the two interfaces is varied from being opposite to same and also with the increasing applied electric field. The increased destabilization is caused by a reverse EPF near the free surface when the interfaces bear the same sign of zeta potentials. Flow reversal by EPF at the free surface occurs at smaller zeta potential of the free surface when the film is thicker because of less influence of the EOF arising at the solid–electrolyte boundary. The amplitude of the surface waves is found to be smaller when the unstable waves travel at a faster speed. The films can undergo pseudo-dewetting when the free surface is almost stationary under the combined influences of EPF and EOF. The free surface instability of the coupled EOF and EPF has some interesting implications in the development of micro/nano fluidic devices involving a free surface.