Ontology Based E-Healthcare Information Retrieval System: A Semantic Approach

With the increase of data in the health care system provides a base for the development of an effective information retrieval system. The implementation of such information retrieval system integrates the heterogeneous information from the healthcare environment. Most of the existing information retrieval systems are syntactic based systems, which will provide inefficient results for the search queries. The objective of this approach is to design a semantic based E-Healthcare information retrieval system. The proposed approach uses an ontology to define the disease-treatment information and will be used for the effective information retrieval. The designated approach is evaluated with a web based tool and the results shows that there is an improvement in the approach

Economic Analysis of HRES Systems with Energy Storage During Grid Interruptions and Curtailment in Tamil Nadu, India:A Hybrid RBFNOEHO Technique

This work presents an economic analysis of a hybrid renewable energy source (HRES) integrated with an energy storage system (ESS) using batteries with a new proposed strategy. Here, the HRES system comprises wind turbines (WT) and a photovoltaic (PV) system. The hybrid WT, PV and energy storage system with battery offer several benefits, in particular, high wind generation utilization rate, and optimal generation for meeting supply-demand gaps. The real recorded data of various parameters of a 22 KV hybrid ‘Regen’ feeder of 110/22 KV Vagarai Substation of TANTRANSCO in Palani of Tamilnadu in India was gathered, studied for the entire year of 2018, and utilized in this paper. The proposed strategy is the hybridization of two algorithms called Radial Basis Function Neural Network (RBFNN) and Oppositional Elephant Herding Optimization (OEHO) named the RBFNOEHO technique. With the help of RBFNN, the continuous load demand required for the HRES and be tracked. OEHO is used to optimize a perfect combination of HRES with the predicted load demand. The aim of the proposed hybrid RBFNOEHO is to study the cost comparison of the HRES system with the existing conventional base method, energy storage method (ESS) with batteries and with HOMER. The proposed Hybrid RBFNOEHO technique is evaluated by comparing it with the other techniques; it is found that the proposed method yields a more optimal solution than the other techniques

Multiple Criteria Decision Making (MCDM) Based Economic Analysis of Solar PV System with Respect to Performance Investigation for Indian Market

Energy market is subject to changing energy demands on a daily basis. The increasing demand for energy necessitates the use of renewable sources and promotes decentralized generation. Specifically, solar PV is preferred in the energy market to meet the increasing energy demand. New approaches are preferred in the economic analysis to simulate multiple actor interplays and intermittent behavior in order to predict the increasing complexity in solar PV. In the Indian society, there are various myths and perceptions regarding economics of electricity generated through solar PV system. Therefore, this paper will address the various Life Cycle Cost Analysis (LCCA) and economic analysis for all types of consumers in the Indian electricity market. A detailed economic and performance study is made by considering ten categories and seven sub categories of investment plan for 1 MW solar projects using Multi Criteria Decision Making (MCDM). Analytic Hierarchy Process (AHP) is applied to support the decision

Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT

Detection of crop diseases is imperative for agriculture to be sustainable. Automated crop disease detection is a major issue in the current agricultural industry due to its cluttered background. Internet of Things (IoT) has gained immense interest in the past decade, as it accumulates a high level of contextual information to identify crop diseases. This study paper presents a novel method based on Taylor‐Water Wave Optimization‐based Generative Adversarial Network (Taylor‐WWO‐based GAN) to identify diseases in the agricultural industry. In this method, the IoT nodes sense the plant leaves, and the sensed data are transmitted to the Base Station (BS) using Fractional Gravitational Gray Wolf Optimization. This technique selects the optimal path for data transmission. After performing IoT routing, crop diseases are recognized at the BS. For detecting crop disease, the input image acquired from the IoT routing phase is then forwarded to the next step, that is, preprocessing, to improve the quality of the image for further processing. Then, Segmentation Network (SegNet) is adapted to segment the images, and extraction of significant features is performed using the acquired segments. The extracted features are adapted by the GAN, which is trained by Taylor‐WWO. The proposed Taylor‐WWO is newly devised by integrating the Taylor series and WWO algorithms. The proposed Taylor‐WWO‐based GAN showed improved performance with a maximum accuracy of 91.6%, maximum sensitivity of 89.3%, and maximum specificity of 92.3% in comparison with existing methods

Small molecule inhibitors of HCV replication from Pomegranate

Hepatitis C virus (HCV) is the causative agent of end-stage liver disease. Recent advances in the last decade in anti HCV treatment strategies have dramatically increased the viral clearance rate. However, several limitations are still associated, which warrant a great need of novel, safe and selective drugs against HCV infection. Towards this objective, we explored highly potent and selective small molecule inhibitors, the ellagitannins, from the crude extract of Pomegranate (Punica granatum) fruit peel. The pure compounds, punicalagin, punicalin, and ellagic acid isolated from the extract specifically blocked the HCV NS3/4A protease activity in vitro. Structural analysis using computational approach also showed that ligand molecules interact with the catalytic and substrate binding residues of NS3/4A protease, leading to inhibition of the enzyme activity. Further, punicalagin and punicalin significantly reduced the HCV replication in cell culture system. More importantly, these compounds are well tolerated ex vivo and `no observed adverse effect level' (NOAEL) was established upto an acute dose of 5000 mg/kg in BALB/c mice. Additionally, pharmacokinetics study showed that the compounds are bioavailable. Taken together, our study provides a proof-of-concept approach for the potential use of antiviral and non-toxic principle ellagitannins from pomegranate in prevention and control of HCV induced complications