Anomaly-Based Intrusion Detection System in RPL by Applying Stochastic and Evolutionary Game Models over IoT Environment

Wireless Personal Communications - The rapid development of Information and Communication Technology and the growing number of devices connected to the Internet make the Internet of Things (IoT) as...     

Investigation on sulphonated zinc oxide nanorod incorporated sulphonated poly (1,4-phenylene ether ether sulfone) nanocomposite membranes for improved performance of microbial fuel cell

Hydrothermally prepared zinc oxide nanorods are sulphonated (S–ZnO NR) and incorporated into 15% Sulphonated Poly (1,4-Phenylene Ether Ether Sulfone) (SPEES) to improve the hydrophilicity, water uptake and ion transfer capacity. Water uptake and ion transfer capacity increased to 34.6 ± 0.6% and 2.0 ± 0.05 meq g^?1 from 29.8 ± 0.3% and 1.4 ± 0.04 meq g^?1 by adding 7.5 wt% S–ZnO NR to SPEES. Morphological studies show the prepared S–ZnO NR is well dispersed in the polymer matrix. SPEES +7.5 wt% S–ZnO NR membrane exhibits optimum performance after three-weeks of continual operation in a fabricated microbial fuel cell (MFC) to produce a maximum power density of 142 ± 1.2 mW m^?2 with a reduced biofilm compared to plain SPEES (59 ± 0.8 mW m^?2), unsulphonated filler incorporated SPEES (SPEES + 7.5 wt% ZnO, 68 ± 1.1 mW m^?2) and Nafion (130 ± 1.5 mW m^?2) thereby suggesting its suitability as a sustainable and improved cation exchange membrane (CEM) for MFCs.     

Biohydrogen Production from Organic Waste – A Review

Hydrogen fuel is a promising alternative to fossil fuels because of its energy content, clean nature, and fuel efficiency. However, it is not readily available. Most current producion processes are very energy intensive and emit carbon dioxide. Therefore, this article reviews technological options for hydrogen production that are eco-friendly and generate clean hydrogen fuel. Biological methods, such different fermentation processes and photolysis are discussed together with the required substrates and the process efficiency.     

Swoop: A Web Ontology Editing Browser

In this paper, we describe Swoop, a hypermedia inspired Ontology Browser and Editor based on OWL, the recently standardized Web-oriented ontology language. After discussing the design rationale and architecture of Swoop, we focus mainly on its features, using illustrative examples to highlight its use. We demonstrate that with its Web-metaphor, adherence to OWL recommendations and key unique features, such as Collaborative Annotation using Annotea, Swoop acts as a useful and efficient Web Ontology development tool. We conclude with a list of future plans for Swoop, that should further increase its overall appeal and accessibility.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

Investigation of long term drift of an intraocular pressure sensor

Microsystem Technologies - “Zero drift” behavior of an optical intraocular pressure sensor is studied using an analytical model based on the deflection of a circular membrane. Results...     

An efficient neural-network model for real-time fault detection in industrial machine

Neural Computing and Applications - Induction machines have extensive demand in industries as they are used for large-scale production and, therefore, vulnerable to both electrical and mechanical...     

Structure-property relations for a phase-pure,nanograined tetragonal zirconia ceramic stabilized with minimum CaO doping

Dense (~97%) CaO-stabilized ZrO₂ ceramic was stabilized with minimum (3 mol%) doping (reported to date) and processed via conventional sintering at a low temperature (~1200°C); compositional analysis via X-ray florescence confirmed the CaO doping accuracy. Phase-pure tetragonal structure (characterized via both X-ray diffraction and Raman spectroscopy) along with uniform nanograins (90 nm) of the ceramic ensured the evolution of no monoclinic phase even after vigorous low-temperature degradation experiments (both thermal and hydrothermal aging for 80-100 h). The sintered ceramic recorded a high hardness (~15 GPa); the indentation toughness value was also comparable to a 3 mol% yttria-stabilized zirconia system. The remarkable structure–property correlations in the 3 mol% CaO-stabilized ZrO₂ ceramic suggests that the same may be worth examining for suitable future applications (e.g., in dental ceramics).