Comparative Analysis of Linear Controllers used for Grid Connected PV System

Requirement for electrical energy is increasing in a ramp function manner. To meet the steady increasing in energy demand it is required to find some alternate source of energy. Except the conventional source of energy one type of renewable energy i.e PV may be regarded as a clean source of energy to meet the energy demand. PV modules generating DC power cannot be directly connected to the electrical infrastructure as most of the grid infrastructure uses either 230volt or 120 volt. Therefore power electronic device most be connected (inverter) between PV and grid. In order to make a competitive market between the renewable generated power and conventional way of generating the power it is required to design a cost effective inverter, qualitative output which is pure sinusoidal and harmonics free. In this paper a comparative analysis among the various linear controllers are presented. Proposed Optimised PID Controller is Presented through MATLAB Simulink based environment

A Real-Time Approach for Smart Building Operations Prediction Using Rule-Based Complex Event Processing and SPARQL Query

Due to intelligent, adaptive nature towards various operations and their ability to provide maximum comfort to the occupants residing in them, smart buildings are becoming a pioneering area of research. Since these architectures leverage the Internet of Things (IoT), there is a need for monitoring different operations (Occupancy, Humidity, Temperature, CO2, etc.) to provide sustainable comfort to the occupants. This paper proposes a novel approach for intelligent building operations monitoring using rule-based complex event processing and query-based approaches for dynamically monitoring the different operations. Siddhi is a complex event processing engine designed for handling multiple sources of event data in real time and processing it according to predefined rules using a decision tree. Since streaming data is dynamic in nature, to keep track of different operations, we have converted the IoT data into an RDF dataset. The RDF dataset is ingested to Apache Kafka for streaming purposes and for stored data we have used the GraphDB tool that extracts information with the help of SPARQL query. Consequently, the proposed approach is also evaluated by deploying the large number of events through the Siddhi CEP engine and how efficiently they are processed in terms of time. Apart from that, a risk estimation scenario is also designed to generate alerts for end users in case any of the smart building operations need immediate attention. The output is visualized and monitored for the end user through a tableau dashboard

DEVELOPMENT AND VALIDATION OF ULTRAVIOLET SPECTROPHOTOMETRIC METHOD FOR QUANTITATIVE ESTIMATION OF FAMOTIDINE IN BULK AND TABLET DOSAGE FORM

  Objectives: The purpose of the study is to develop a simple, precise, economical, accurate, reproducible, and sensitive method for the estimation of famotidine (FAM) in bulk and its pharmaceutical dosage forms by ultraviolet (UV) absorption spectrophotometry.Methods: The method uses 0.1 N HCl, pH 1.20 as a solvent for the quantitative estimation of FAM in bulk and its tablets dosage form by UV absorption spectrophotometry.Results: FAM exhibited absorbance maxima at 266 nm in 0.1 N HCl, pH 1.20 solvent. The developed method was validated as per the ICH analytical method validation guidelines. Beer's law was obeyed in range of 0-30 μg/ml with r2=0.9998. The limit of detection and limit of quantification values of FAM were found to be 0.152 and 0.461 μg/ml, respectively. The mean percentage recovery for developed method was found to be in the range of 99.35-99.48%, respectively, for the marketed dosage forms. The developed method was also found to be robust and ensures bench-top stability.Conclusion: The developed method was found to be suitable for the routine quantitative analysis of FAM in bulk and pharmaceutical dosage form. It was also concluded that developed UV spectrophotometry method was accurate, precise, linear, reproducible, robust, and sensitive

FORMULATION AND EVALUATION OF FAMOTIDINE MICRO BALLOONS WITH ENHANCED ANTI-ULCER ACTIVITY

Objective: The aim of the present study was to formulate and optimize famotidine loaded micro balloons for enhancing bioavailability, increasing gastric residence time of drug and to achieve sustained release in the stomach.Methods: Microballoons were prepared using emulsion solvent diffusion method using HPMC K4M as the polymer. All the formulated microspheres were subjected to various evaluation parameters such as % drug entrapment, micromeritics properties, % buoyancy and in vitro drug release studies. The formulation was optimized using 32 full factorial design. Optimized formulation was subjective to in vivo floating (X-ray) and in vivo antiulcer studies.Results: The microballoons were smooth and spherical in shape and were porous in nature due to hollow cavity. Sustained/controlled release of drug was observed for more than 12 h. based on the results of % drug entrapment, in vitro drug release and % buoyancy studies, formulation F6 was selected as optimized formulation. The release kinetics of optimized formulation followed Higuchi model and mechanism of release was non-Fickian diffusion. Examination of the X-ray radiographic images taken during the study indicated that the optimized formulation remained buoyant and uniformly distributed in the gastric contents for a long period. In ethanol-induced ulcer model, drug-loaded microballoons treated group showed significant ulcer protection index of 83.26% as compared to the marketed brand of famotidine 76. 09% and untreated control group.Conclusion: Famotidine-loaded floating micro balloons were successfully prepared and prove to be useful for the prolonged gastric residence of the drug, better bioavailability, patient compliance and anti-ulcer activity

A Decision Support System for Liver Diseases Prediction: Integrating Batch Processing, Rule-Based Event Detection and SPARQL Query

Liver diseases pose a significant global health burden, impacting a substantial number of individuals and exerting substantial economic and social consequences. Rising liver problems are considered a fatal disease in many countries, such as Egypt, Molda, etc. The objective of this study is to construct a predictive model for liver illness using Basic Formal Ontology (BFO) and detection rules derived from a decision tree algorithm. Based on these rules, events are detected through batch processing using the Apache Jena framework. Based on the event detected, queries can be directly processed using SPARQL. To make the ontology operational, these Decision Tree (DT) rules are converted into Semantic Web Rule Language (SWRL). Using this SWRL in the ontology for predicting different types of liver disease with the help of the Pellet and Drool inference engines in Protege Tools, a total of 615 records are taken from different liver diseases. After inferring the rules, the result can be generated for the patient according to the DT rules, and other patient-related details along with different precautionary suggestions can be obtained based on these results. Combining query results of batch processing and ontology-generated results can give more accurate suggestions for disease prevention and detection. This work aims to provide a comprehensive approach that is applicable for liver disease prediction, rich knowledge graph representation, and smart querying capabilities. The results show that combining RDF data, SWRL rules, and SPARQL queries for analysing and predicting liver disease can help medical professionals to learn more about liver diseases and make a Decision Support System (DSS) for health care

DEVELOPMENT AND VALIDATION OF UV SPECTROPHOTOMETRIC METHOD FOR QUANTITATIVE ESTIMATION OF LAFUTIDINE IN BULK AND PHARMACEUTICAL DOSAGE FORM

Objective: The objectives of the present research was to develop a simple, precise, economical, accurate, reproducible and sensitive method for the quantitative estimation of lafutidine in bulk and its pharmaceutical dosage forms by Ultra Violet (UV) absorption spectrophotometry.Methods: The method uses 0.1 N HCl, pH 1.20 as a solvent of choice for the quantitative estimation of lafutidine in bulk and its tablets dosage form by UV absorption spectrophotometry at a wavelength of 290 nm. The method was validated for parameters like linearity, range, precision, Limit of Detection (LOD), Limit of Quantification (LOQ), accuracy, recovery and stability of the analyte.Results: Lafutidine exhibited absorbance maxima at 290 nm in 0.1 N HCl, pH 1.20 solvent. The developed method was validated as per the ICH validation guidelines. Beer's law was obeyed in range of 0-30 µg/ml with r2= 0.9997. The LOD and LOQ values of lafutidine were found to be 0.545 µg/ml and 1.654 µg/ml respectively. The mean % recovery for the developed method was found to be in the range of 99.25 to 99.45 % respectively for the marketed dosage forms. The developed method was also found to be robust.Conclusion: The developed method was found suitable for the routine quantitative analysis of lafutidinein bulk and pharmaceutical dosage form. It was also concluded that developed UV spectrophotometry method was accurate, precise, linear, reproducible, robust and sensitive

Hybrid Taguchi-GRA-CRITIC Optimization Method for Multi-Response Optimization of Micro-EDM Drilling Process Parameters

In this study, an attempt is made to investigate how the operational parameters such as capacitance, voltage, feed rate, and rotating speed affect the material removal rate, tool wear, overcut, and taper angle for micro-EDM drilling of aluminium 6061 utilizing brass C360 electrode. A novel Taguchi-GRA-CRITIC hybrid optimization methodology is used to obtain the optimal combination of micro-EDM drilling process parameters. The experiment was designed using the Taguchi L18 orthogonal array, and responses were recorded for each experiment. Grey Relational Analysis (GRA) is applied to improve the multi-response of the planned experiment. The weighting values corresponding to various responses are determined using CRITIC (criterion importance through intercriteria correlation) analysis. The hybrid methodology determines the best combination of process parameters for different responses. ANOVA was used to discover the most critical parameters. Finally, confirmation experiments were conducted with optimal parameters to identify improvement in grey relational grade over the initial parameters. The study\u27s findings indicate that, compared to the initial process parameter setting, the grey relational grade (GRG) increased by 92.36% with the optimal parameter setting

EFFECT OF TILLAGE, RESIDUE AND NUTRIENT MANAGEMENT ON SOIL qualities AND YIELD PARAMETERS OF RICE

A field experiment was conducted at Rampur, Nepal to see the effect of tillage, residue and nutrient management practices on soil properties and grain yield of rice. Three factors each with two levels i.e. tillage (with or without), residue (with or without) and nutrient management (recommended dose (RD) with 100:60:30 NPK kg ha-1 and farmer’s doses (FD) with 5Mt ha-1 of FYM + 50:23:0 NPK kg ha-1. Thus, altogether eight treatment combinations were evaluated under strip-split plot design with three replications. Higher soil organic matter was recorded in residue kept (5.73%) than the residue removed plots. Exchangeable potassium was found higher in no tillage (110.52 kg ha-1) than the conventional tillage (76.77 kg ha-1). Number of effective tillers was higher in no tillage; residue kept and recommended doses of fertilizer. Grain yield was significantly higher in no tillage with 3.66 Mt and residue kept with 3.72 Mt ha-1 compared to conventional tillage with 2.28 Mt and residue removed plots having 2.22 Mt ha-1. RD produced significantly higher grain yield of 4.53 Mt ha-1 than FD with 1.41 Mt ha-1. Therefore, untilled direct seeded rice with residue and recommend does of nutrients seem promising in Terai region of Nepal