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.

     

Validity as a Measure of Data Quality in Internet of Things Systems

Data quality became significant with the emergence of data warehouse systems. While accuracy is intrinsic data quality, validity of data presents a wider perspective, which is more representational and contextual in nature. Through our article we present a different perspective in data collection and collation. We focus on faults experienced in data sets and present validity as a function of allied parameters such as completeness, usability, availability and timeliness for determining the data quality. We also analyze the applicability of these metrics and apply modifications to make it conform to IoT applications. Another major focus of this article is to verify these metrics on aggregated data set instead of separate data values. This work focuses on using the different validation parameters for determining the quality of data generated in a pervasive environment. Analysis approach presented is simple and can be employed to test the validity of collected data, isolate faults in the data set and also measure the suitability of data before applying algorithms for analysis. On analyzing the data quality of the two data sets on the basis of above-mentioned parameters. We show that validity for data set 1 was found to be 75% while it was found to be 67% only for data set 2. Availability and data freshness metrics performance were analyzed graphically. It was found that for data set 1, data freshness was better while availability metric was found better for data set 2. Usability obtained for data set 2 was 86% which was higher as compared to data set 1 whose usability metric was 69%. Thus, this work presents methods that can be leveraged for estimating data quality that can be beneficial in various IoT based industries which are essentially data centric and the decisions made by them depends upon the validity of data.

     

Enhancement of Tensile and Microhardness of AA 6082-T6 Friction Stir Welds via Brass Interlayers

Russian Journal of Non-Ferrous Metals - This paper investigates the effects of brass interlayer on the microstructural and mechanical properties of friction stir welded AA 6082-T6. To analyze the...     

Modeling and simulation of temperature drift for ISFET-based pH sensor and its compensation through machine learning techniques

The paper presents modeling and simulation of ion-sensitive field-effect transistor (ISFET)-based pH sensor with temperature-dependent behavioral macromodel and proposes to compensate the temperature drift in the sensor using intelligent machine learning (ML) models. The macromodel is built using SPICE by introducing electrochemical parameters in a metal-oxide-semiconductor field-effect transistor (MOSFET) model to simulate ISFET characteristics. We account for the temperature dependence of electrochemical and semiconductor parameters in our macromodel to increase its robustness. The macromodel is then exported as a subcircuit element, which is used to design the readout interface circuit. A simple constant-voltage, constant-current (CVCC) topology is utilized to generate the data for temperature drift in ISFET pH sensor, which is used to train and test state-of-the-art ML-based regression models in order to compensate the drift behavior. The experimental results demonstrate that the random forest (RF) technique achieves the best performance with very high correlation and low error rate. Corresponding curves for output signal using the trained models show highly temperature-independent characteristics when tested for pH 2, 4, 7, 10, and 12, and we obtained a root mean squared error (RMS) variation of ΔpH ≤ 0.024 over a temperature range of 15°C to 55°C in comparison with ΔpH ≤ 1.346 for uncompensated output signal. This work establishes the framework for integration of ML techniques for drift compensation of ISFET chemical sensor to improve its performance.     

Experimental analysis of a two‐axis tracking system for solar parabolic dish collector

In this paper, an attempt has been made to develop a two‐axis tracking system for solar parabolic dish concentrator and experimentally evaluated the performance of the tracking system. In this proposed design, the sensor design uses the illumination produced by the convex lens on the apex of a pyramid to align the dish in‐line with the sun. The change in incident angle of the solar rays on the lens surface shifts the area of illumination from the apex of the pyramid towards its faces. Photodiodes placed on the faces of the pyramid are used as the sensitive elements to detect the movement of the sun. The sensor output is fed to a microcontroller‐based system to drive the stepper motor on the basis of the programmed algorithm such that it receives normal incidence of sunlight on the sensor. To evaluate the performance of the proposed system, a conventional available 1‐W photovoltaic (PV) panel is placed at the focal point to measure the short circuit current and open circuit voltage. With respect to the conventional solar PV panel, it is observed that the positioning accuracy of the proposed tracking system enhances the short circuit current of 0.11 A by 86%. Thus, the proposed tracking system can be used in a stand‐alone parabolic dish with concentrating PV module as the focal point for further studies.     

A review and recent developments on strategies to improve the photocatalytic elimination of organic dye pollutants by BiOX (X=Cl,Br, I,F) nanostructures

The main environmental problems associated with water body pollution are typically those caused by the discharge of untreated effluents released by various industries. Wastewater from the textile dye industry is itself a large contributor and contains a huge number of complex components, a wide spectrum of organic pollutants with high concentration of biochemical oxygen demand (BOD)/chemical oxygen demand (COD) and other toxic elements. One of several potential techniques to degrade such reactive dyes before being discharged to water bodies is photocatalysis, and bismuth-based photocatalysts are rapidly gaining popularity in this direction. Bismuth oxyhalides, BiOX (X=Cl, Br, I, F), as a group of ternary compound semiconductors (V-VI-VII), have been explored extensively for their photocatalytic activity due to their unique crystal lattice with special layered structure in pure as well as modified form. With suitable band gap and band edge positions, which are a required condition for efficient water breakup and high photon absorption, BiOCl scores over other oxyhalides. Photocatalytic activity depends on many factors such as synthesis method, morphology, size, illumination type, dye choice among others. This paper gives a critical review on bismuth oxyhalides as a family on various aspects of modifications such as doping (with unique and interesting metals as well), morphology and synthesis parameters, polymer and carbon assisted composites in order to further enhance the photocatalytic efficiency in UV/visible region of solar spectrum.     

A Comprehensive Neural Network Model for Colorization and Captioning of Images Along with IoT Deployment

The convergence of artificial neural networks and the internet of things (IoT) has gained popularity in the field of computer science research. In this work, an efficient neural network model for the image colorization problem is proposed along with deploying these models to the remote system using IoT deployment tools. Further, this work proposed two convolution neural network models namely the Alpha model and Beta model towards solving the image colorization of the grayscale format. An efficient combination of models is proposed and analyzed such that the loss rate is minimized as?~?0.005. Next, an efficient model for solving image captioning is proposed based on the bi-directional long short term memory model. Finally, the work discusses the merits and demerits of deploying the neural network model using the AWS Greengrass and Docker IoT environment on remote systems.

     

Polymeric Films Containing Sodium Chlorite That Release Disinfectant Gas upon Activation with UV Light

Polymeric films that release disinfectant gas on demand have the potential to be useful for management of microbial burden (e.g., sterilization). Past attempts to create such films, however, have suffered from the need for stringent control over moisture or exposure to visible light prior to use. It is reported that polyvinyl alcohol (PVA) or polyolefin (POD) films that contain NaClO₂ crystals can release ClO₂ gas upon UV‐activation and exposure to moisture. In addition to showing that the concentration of gaseous ClO₂ released from the polymeric films is sufficiently high for antimicrobial activity, fundamental insights into factors controlling ClO₂ release are provided by using atomic force microscopy, optical microscopy, Raman microscopy, and time‐of‐flight secondary ion mass spectrometry. Specifically, by determining the sizes of the polymer‐dispersed NaClO₂ particles, support for the hypothesis that UV light activates an interfacial layer of the NaClO₂ crystals to generate ClO₂ is obtained. Additionally, it is found that the half‐life of the UV‐activated state of NaClO₂ depends on the reactivity of the polymer matrix. Because both PVA and POD possess properties analogous to polymers used in packaging films, it is concluded that the approach described in this study may enable introduction of deodorizing or antimicrobial functional properties into polymeric packaging.     

Multifunctional temperature-responsive polymers as advanced biomaterials and beyond

The versatility and applicability of thermoresponsive polymeric systems have led to great interest and a multitude of publications. Of particular significance, multifunctional poly(N-isopropylacrylamide) (PNIPAAm) systems based on PNIPAAm copolymerized with various functional comonomers or based on PNIPAAm combined with nanomaterials exhibiting unique properties. These multifunctional PNIPAAm systems have revolutionized several biomedical fields such as controlled drug delivery, tissue engineering, self-healing materials, and beyond (e.g., environmental treatment applications). Here, we review these multifunctional PNIPAAm-based systems with various cofunctionalities, as well as highlight their unique applications. For instance, addition of hydrophilic or hydrophobic comonomers can allow for polymer lower critical solution temperature modification, which is especially helpful for physiological applications. Natural comonomers with desirable functionalities have also drawn significant attention as pressure surmounts to develop greener, more sustainable materials. Typically, these systems also tend to be more biocompatible and biodegradable and can be advantageous for use in biopharmaceutical and environmental applications. PNIPAAm-based polymeric nanocomposites are reviewed as well, where incorporation of inorganic or carbon nanomaterials creates synergistic systems that tend to be more robust and widely applicable than the individual components. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48770.     

LAG-3, TIM-3 and VISTA Expression on Tumor-Infiltrating Lymphocytes in Oropharyngeal Squamous Cell Carcinoma—Potential Biomarkers for Targeted Therapy Concepts

Tumor growth and survival requires a particularly effective immunosuppressant tumor microenvironment (TME) to escape destruction by the immune system. While immunosuppressive checkpoint markers like programmed cell death 1 ligand (PD-L1) are already being targeted in clinical practice, lymphocyte-activation-protein 3 (LAG-3), T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) and V-domain Ig suppressor of T cell activation (VISTA) inhibitors are currently under investigation in clinical trials. Reliable findings on the expression status of those immune checkpoint inhibitors on tumor-infiltrating lymphocytes (TILs) in the TME of oropharyngeal squamous cell carcinoma (OPSCC) are lacking. This work aims to describe the expression of LAG-3, TIM-3, and VISTA expression in the TME of OPSCC. We created a tissue microarray of paraffin-embedded tumor tissue of 241 OPSCC. Expression of the immune checkpoint protein LAG-3, TIM-3, and VISTA in OPSCC was evaluated using immunohistochemistry and results were correlated with CD8+ T-cell inflammation and human papillomavirus (HPV)-status. 73 OPSCC stained positive for LAG-3 (31%; HPV+:44%; HPV-:26%, p = 0.006), 122 OPSCC stained positive for TIM-3 (51%; HPV+:70%; HPV-:44%, p < 0.001) and 168 OPSCC (70%; HPV+:75%; HPV-:68%, p = 0.313) for VISTA. CD8+ T-cells were significantly associated with LAG-3, TIM-3 and VISTA expression (p < 0.001, p < 0.001, p = 0.007). Immune checkpoint therapy targeting LAG-3, TIM-3, and/or VISTA could be a promising treatment strategy especially in HPV-related OPSCC. Future clinical trials investigating the efficacy of a checkpoint blockade in consideration of LAG-3, TIM-3, and VISTA expression are required.