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.     

Smart antenna design for high‐speed moving vehicles with minimum return loss

The Internet of Things (IoT) is a connection amongst people and applications to another dimension of machine‐to‐machine communication. IoT scenario is unequivocally related with the development of the advancement of wireless sensor systems (WSNs) and radio‐frequency identification (RFID) frameworks. Owing to the technological advances around the world, energy demand is increasing exponentially. Energy proficiency has turned out to be one of the real worries in the present life that essentially influence every single human action. In communication system, return loss is a major issue for transmission process. Owing to return loss, a huge amount of power consumption occurs. This phenomenon is contemporary with transmission process, and it will initiate a serious problem for high‐speed moving substance like aircraft, rockets, and spaceship. To overcome this problem, a four‐element cylindrical antenna (conformal) array with better axial radiation is proposed. The four U‐shaped slots are uniformly wrapped around on a cylindrical surface, which produces tilted radiation. To enhance the axial radiation, four conformal elements are reefed by a one‐ to four‐microstrip feed network. The proposed conformal design has a bandwidth of 200 MHz (narrow bandwidth) at the center frequency of 3.9 GHz, covering the range of 3 to 3.9 GHz, with the gain of 4.9 dBic, and can be suitable for unmanned aerial vehicles (UAV), wireless avionics intra‐communication (WAIC), and so forth. The proposed design is low profile and can be used for high‐speed avionic applications. Finally, machine learning technique is explored to design a model for a smart antenna with optimistic parameters to reduce return loss and enhance the transmission rate.     

Metal ion sensing and light activated antimicrobial activity of aloe-vera derived carbon dots

Carbon dots (CDs) have emerged out as a potential material amongst the carbon family for a wide range of applications including chemical/biological sensing, photocatalysis, bioimaging, etc. The green synthesis of these CDs from natural sources is gaining the significant interest of peer community for their wide utility. Herein, we present a facile one-step pyrolysis method for CDs synthesis from Aloe-Vera extract, which show bright blue luminescence under UV light with a quantum yield of 12.3%. Further, ex-situ morphological, structural and optical characterizations reveal their high quality and excitation independent emission behavior with the presence of carboxyl, hydroxyl functional groups. Furthermore, these CDs were studied for Fe(III) sensing in water without any surface modifications and assessed for their light activated antibacterial activity against E.Coli and Staphylococcus aureus.     

E-Learning during COVID-19 Outbreak: Cloud Computing Adoption in Indian Public Universities

In the COVID-19 pandemic situation, the need to adopt cloud computing (CC) applications by education institutions, in general, and higher education (HE) institutions, in particular, has especially increased to engage students in an online mode and remotely carrying out research. The adoption of CC across various sectors, including HE, has been picking momentum in the developing countries in the last few years. In the Indian context, the CC adaptation in the HE sector (HES) remains a less thoroughly explored sector, and no comprehensive study is reported in the literature. Therefore, the aim of the present study is to overcome this research vacuum and examine the factors that impact the CC adoption (CCA) by HE institutions (HEIs) in India. The scope of the study is limited to public universities (PUs) in India. There are, in total, 465 Indian PUs and among these 304 PUs, (i.e., 65% PUs) are surveyed using questionnaire-based research. The study has put forth a novel integrated technology adoption framework consisting of the Technology Acceptance Model (TAM), Technology-Organization-Environment (TOE), and Diffusion of Innovation (DOI) in the context of the HES. This integrated TAM-TOE-DOI framework is utilized in the study to analyze eleven hypotheses concerning factors of CCA that have been tested using structural equation modelling (SEM) and confirmatory factor analysis (CFA). The findings reveal that competitive advantage (CA), technology compatibility (TC), technology readiness (TR), senior leadership support, security concerns, government support, and vendor support are the significant contributing factors of CCA by Indian PUs. The study contends that whereas the rest of the factors positively affect the PUs’ intention towards CCA, security concerns are a significant reason for the reluctance of these universities against adopting CC. The findings demonstrated the application of an integrated TAM-TOE-DOI framework to assess determining factors of CCA in Indian PUs. Further, the study has given useful insights into the successful CCA by Indian PUs, which will facilitate eLearning and remote working during COVID-19 or similar outbreak.     

Correction to: Superconducting Transport Properties of NiFe Artificial Spin Ice and Nb Hybrid Structure

Journal of Superconductivity and Novel Magnetism -     

The role of electrical property in determining the response of 20H-80S composite thin films fabricated for biological applications

Journal of Materials Science - The exploration of exquisite electrical properties of biomaterials for clinical applications is driven by natural design. Inspired by the idea, composite thin films...     

Application of Heuristic Approaches for Prediction of Hydrological Drought Using Multi-scalar Streamflow Drought Index

Water Resources Management - Quantification and prediction of drought events are important for planning and management of water resources in coping with climate change scenarios at global and local...     

HEART: Unrelated parallel machines problem with precedence constraints for task scheduling in cloud computing using heuristic and meta-heuristic algorithms

Cloud computing is becoming a profitable technology because of it offers cost-effective IT solutions globally. A well-designed task scheduling algorithm ensures the optimal utilization of clouds resources and reducing execution time dynamically. This research article deals with the task scheduling of inter-dependent subtasks on unrelated parallel computing machines in a cloud computing environment. This article considers two variants of the problem-based on two different objective function values. The first variant considers the minimization of the total completion time objective function while the second variant considers the minimization of the makespan objective function. Heuristic and meta-heuristic (HEART) based algorithms are proposed to solve the task scheduling problems. These algorithms utilize the property of list scheduling algorithm of unrelated parallel machine scheduling problem. A mixed integer linear programming (MILP) formulation has been provided for the two variants of the problem. The optimal solution is obtained by solving MILP formulation using A Mathematical Programming Language (AMPL) software. Extensive numerical experiments have been performed to evaluate the performance of proposed algorithms. The solutions obtained by the proposed algorithms are found to out-perform the existing algorithms. The proposed algorithms can be used by cloud computing service providers (CCSPs) for enhancing their resources utilization to reduce their operating cost.     

Fatty Acids in Vernonia Produced in the Mid-Atlantic Region of the United States

Vernonia galamensis [(Cass.) Less.] is a native of Ethiopia and Eritrea. Seed of vernonia contain substantial quantities of naturally epoxidized oil, which is used in the paint industry to reduce emissions of volatile organic compounds that produce smog resulting from the use of petroleum-based (alkyd-resin) paint. Epoxidized oil is also used in the manufacture of plasticizers, additives to polyvinyl chloride, polymer blends and coatings, and cosmetic and pharmaceutical applications. Previous research has indicated that vernonia has potential for commercialization in the mid-Atlantic region of the United States. This study characterized fatty acids in oil from vernonia grown in this latter region. Vernonia oil, from 14 vernonia lines grown during 1995 and 1996 under field conditions in Virginia, contained 3.3, 3.0, 5.0, 15.0, 0.2, 0.5, 0.4, and 72.7%, respectively, of C16:0, C18:0, C18:1, C18:2, C18:3, C20:0, C20:1, and vernolic (C18:1 epoxy) fatty acids. Effects of genotypes on vernonia oil quality were generally not significant whereas the effects of years were significant. The concentration of vernolic acid was positively correlated with oil concentration but negatively correlated with concentrations of all individual fatty acids, except for C18:3. Contribution of Virginia State University Agricultural Research Station, journal article series number 253. The use of any trade names or vendors does not imply approval to the exclusion of other products or vendors that may also be suitable.