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.

     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Series equivalence/operation of current-controlled boost-typesingle-phase voltage source converters for bidirectional power flow

Single-phase voltage source power converters (VSCs) under consideration are AC-DC current-controlled boost-type power converters with bidirectional power-handling capability. Equivalence between two series-connected two-level power converters and a single three-level power converter is considered here. Further considered is the series operation of three-level power converters. Simulation results and experimental verification for both are provided. Economical configurations of three-level power converters leading to multilevel waveforms are presented thereafter     

Simulation of frequency nonselective mobile channel with LOScomponent: a deterministic approach

A deterministic digital simulation model with finite sum of properly weighted sinusoids is used to simulate a frequency nonselective mobile channel with LOS component. Measurement data are used to optimise the parameters. Which are then used in the deterministic simulation model. The probability distribution and level cross rate (LCR) obtained from the measured data agree well with the analytical and simulation results     

Cell-mediated cytotoxicity: a predictor of chronic rejection in pediatric HLA haploidentical renal transplants

BACKGROUND: Recipient antidonor cytotoxic T-cell activity has been associated with graft loss and acute rejection in renal allograft recipients. The role of immunologic mechanisms in the development of chronic graft rejection is controversial. We analyzed all living related renal transplants performed at Children's Hospital (Boston, MA) from 1983 to 1995 to assess whether cell-mediated cytotoxicity, determined in vitro and measured before transplantation, was predictive of chronic rejection. METHODS: Eighty-three patients were studied retrospectively. Fifty-seven patients with one haplotype-matched renal transplants from living related donors were studied to determine the association between cell-mediated lympholysis (CML) level, acute rejection, chronic rejection, and graft failure. Acute rejection was defined by the decision to treat. Chronic rejection was defined by histology and/or the absolute serum creatinine value using an increasing serum creatinine level >1.0 mg/dl for children less than 3, a creatinine level >1.5 mg/dl for children between 3 and 10 years of age, and a creatinine level >2.0 mg/dl for children above 10 years of age. Return to dialysis or retransplantation was considered graft failure. RESULTS: Of the 57 haploidentical patients, there were 33 males and 24 females. The mean age at transplant was 11.1 years (SD=6.7). Twelve patients developed chronic rejection, 24 patients developed acute rejection, and 7 patients had graft failure. Pretransplant cytotoxic T lymphocyte activity was associated with chronic rejection (P=0.001) and graft failure (P=0.013) but only marginally with acute rejection (P=0.058). Controlling for age and sex, Cox's proportional hazards model revealed that CML level was predictive of time to chronic rejection (P<0.01) but not acute rejection (P=0.11). It was estimated that every 1-unit increase in CML level raises the monthly risk of chronic rejection by 7%. Ten children received HLA-identical kidneys from their siblings. There were no episodes of chronic rejection after 5 years. Two patients with high CML levels had episodes of acute rejection; both patients responded to treatment. CONCLUSION: Our data demonstrate an association between pretransplant cell-mediated cytotoxicity and the occurrence of chronic rejection in living related one-haploidentical renal transplants in pediatric patients.     

Viscous behaviour of glass-forming liquids: a thermodynamic approach

The temperature dependence of the viscosity of the undercooled melts exhibits an important role in the study of nucleation, crystal growth and the glass-forming ability of materials. Several attempts have been made to study the viscous behaviour of the glass-forming melts and these investigations are mainly based on free volume theory as well as on the configurational entropy model. In the present investigation, an attempt has been made to correlate the thermodynamic parameters with the viscosity of the glass-forming melts and to study the temperature dependence of the viscosity of undercooled liquids on the basis of the free volume theory as well as on the basis of the configurational entropy model of Adam and Gibbs. The entire study is confined on the expression for thermodynamic parameters reported by the authors recently. The expression obtained has been successfully applied to study the temperature dependence of the viscosity of the metallic, molecular and oxide glass-forming liquids.     

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.     

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.     

Ongoing verification of a multiphysics community code: FLASH

When developing a complex, multi‐authored code, daily testing on multiple platforms and under a variety of conditions is essential. It is therefore necessary to have a regression test suite that is easily administered and configured, as well as a way to easily view and interpret the test suite results. We describe the methodology for verification of FLASH, a highly capable multiphysics scientific application code with a wide user base. The methodology uses a combination of unit and regression tests and an in‐house testing software that is optimized for operation under limited resources. Although our practical implementations do not always comply with theoretical regression‐testing research, our methodology provides a comprehensive verification of a large scientific code under resource constraints.Copyright © 2013 John Wiley & Sons, Ltd.