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.

     

Laboratory Experiments on Electroosmotic Dewatering of Vegetable Sludge and Mine Tailings

Vegetable wastes in the food industry are costly lo handle because of their high moisture content. while mill plant tailings in the mining industry contain large quantities of ultralines which are difficult io dewater.This paper describes the results of small scale electmosmotic dewatering (EOD) and combined field dewatering (CFD) measurements with model vegetable sludges and mine tailings.     

STEAM DRYING TECHNOLOGIES: JAPANESE R&D

This report reviews some fundamental and practical aspects of steam drying technologies based mainly on studies published in Japan. Steam drying kinetics, and some industrial technologies particularly for drying of foods, textiles and sludges are reviewed with focus on quality of dried material, drying time, dryer selection and energy recovery from steam dryer exhaust. For energy recovery, heat pump technologies are outlined along with characteristics of different types of steam compressors. A new process is proposed for steam drying; it combines a direct-indirect dryer followed by a direct steam dryer for internal moisture removal.     

Discrete Modeling and Suggested Measurement of Heat Transfer in Gas-Solids Flows

This article presents a two-dimensional transient model for gas-solids flow and heat transfer through pipes using the coupled Computational Fluid Dynamics and Discrete Element Method approach. Numerical simulations have been conducted to examine the modification of fluid thermal structure due to the presence of particles in a pneumatic transport pipeline. Modeled results have demonstrated the key role of transversal motion of rebounding particles in the pipe cross section in altering fluid temperature. Further implementation of this modeling technique in air-drying processes is discussed and possible experimental methods for the measurement of in situ particle and fluid motion and temperature profile are cited.     

The Effect of Moisture Content on the Conversion of Ergosterol to Vitamin D in Shiitake Mushrooms

The distribution of ergosterol in different parts of shiitake mushrooms was studied in order to optimize the conversion of ergosterol to vitamin D₂ during drying. The effect of moisture on the conversion of ergosterol to vitamin D₂ was also investigated by adjusting the moisture content of fresh mushrooms to different levels in a large vacuum desiccator and subjecting them to UV irradiation at 290-320 nm wavelength, for 2 h. The moisture, ergosterol and vitamin D₂ contents were determined using standard procedures. It was found that the ergosterol content on a dry matter basis of fresh shiitake mushroom was highest in the gills (10.6 ± 0.99 mg/g DM), followed by the cap or pileus (5.34 ± 0.64 mg/g DM) and was least in the stalk or stipe (2.97 ± 0.56). The moisture content had a marked influence on the conversion of ergosterol to vitamin D₂, the best conversion taking place at a moisture content of about 70% on a wet basis.