Optimal Automatic Generation Control of Asynchronous Power Systems Using Output Feedback Control Strategy with Dynamic Participation of Wind Turbines

Abstract—This article presents the design of optimal output feedback automatic generation control regulators for an interconnected power system with dynamic participation of doubly fed induction generator based wind turbines. The power systems consist of plants with hydro-thermal turbines and are interconnected via parallel AC/DC links. Efforts have been made to propose optimal automatic generation control regulators based on feedback of output state variables, which are easily accessible and available for the measurement. The designed optimal output feedback automatic generation control regulators are implemented, and the system dynamic responses for various system states are obtained considering 1% load perturbation in one of the areas. The dynamic performance is compared with that obtained with optimal automatic generation control regulators designed using full state vector feedback. The pattern of closed-loop eigenvalues is also determined to test the system stability.     

Facile Synthesis of Ferrocene-Based Polyamides and Their Organic Analogues Terpolyamides: Influence of Aliphatic and Aromatic Sequences on Physico-Chemical Characteristics

Efforts have been devoted to synthesize and characterize processable polymers with desired properties. Herein, four different series of aromatic and aliphatic terpolyamides were prepared via solution phase polycondensation of 4,4′-oxydianiline and hexamethylenediamine (HMDA) with various diacids chlorides (isophthalyol dichloride, terepthalyol dichloride, 1, 1′-ferrocene dicarboxylic acid chloride and trans-azobenzene-4, 4′-dicarbonyl chloride). The structural, morphological and physico-chemical nature of as prepared polymers was explored by Fourier-transform infrared spectroscopy, scanning electron microscopy, thermal analysis (TGA and DSC), and wide-angle x-ray diffraction. Moreover, an aliphatic diamine was incorporated in varying concentration as a flexible methylene spacer and the effect of its concentration on the properties of polyamides was also studied. Changes in various physico-chemical properties such as solubility, inherent viscosity, surface morphology and flame retarding behaviour were investigated. Marked difference in morphology and solubility was observed with the change in the ratio of segments in the chain. Inherent viscosities of polymers ranged from 1.8052–1.6274 dl/g indicating reasonably moderate molecular weights. Interestingly, ferrocene based aromatic polymers were more thermally stable (T_g 260 °C, T_i 310 °C, T_h 525 °C, T_f 720 °C, for PF₀), and also found to exhibit best flame retarding behavior (limiting oxygen index value for PF₀is LOI 33.15%).

     

A Novel Sprague-Dawley Rat Model Presents Improved NASH/NAFLD Symptoms with PEG Coated Vitexin Liposomes

Chronic liver disease (CLD) is a global threat to the human population, with manifestations resulting from alcohol-related liver disease (ALD) and non-alcohol fatty liver disease (NAFLD). NAFLD, if not treated, may progress to non-alcoholic steatohepatitis (NASH). Furthermore, inflammation leads to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Vitexin, a natural flavonoid, has been recently reported for inhibiting NAFLD. It is a lipogenesis inhibitor and activates lipolysis and fatty acid oxidation. In addition, owing to its antioxidant properties, it appeared as a hepatoprotective candidate. However, it exhibits low bioavailability and low efficacy due to its hydrophobic nature. A novel rat model for liver cirrhosis was developed by CCL4/Urethane co-administration. Vitexin encapsulated liposomes were synthesized by the ‘thin-film hydration’ method. Polyethylene glycol (PEG) was coated on liposomes to enhance stability and stealth effect. The diseased rats were then treated with vitexin and PEGylated vitexin liposomes, administered intravenously and orally. Results ascertained the liposomal encapsulation of vitexin and subsequent PEG coating to be a substantial strategy for treating liver cirrhosis through oral drug delivery.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Optical,DC and AC electrical investigations of 4-hydroxy coumarin molecule as an organic Schottky diode

The current–voltage (I–V) and optical characteristics of 4-hydroxy coumarin Schottky diode were investigated. The conventional methods related with device were used to extract the various diode parameters. From dielectric study low dielectric constant and loss was observed. From its optical study, an indirect allowed transition is shown by this compound. The optical band gap (E _g ) was found to be around 3.78 eV. The observed properties shown by this molecule give a bright opportunity to explore its application for different organic devices.     

Determination of lithium isotopic composition by thermal ionization mass spectrometry

A mass spectrometric method has been proposed for the determination of the isotopic composition of lithium. It is based upon thermal ionization of LiOH loaded onto a single SiO2-coated Re filament. By this method, stable emissions of Li+ ion have been achieved for an extended period of time. The proposed method is capable of analyzing trace quantities (approximately 40 ng) of Li in the presence of sodium with an uncertainty of +/-0.000 25 (two standard deviations of the mean).     

Indoor radon levels and lung cancer risk estimates in seven cities of the Bahawalpur Division, Pakistan

Indoor radon concentration levels were measured in seven major cities of the Bahawalpur Division, Pakistan. These included Fort Abbas, Minchin Abad, Hasilpur, Bahawalpur, Liaqatpur, Rahimyar Khan and Sadiq Abad. In order to select houses for this survey, the inhabitants were approached through their school-registered children. Due to several constraints, only those 100 houses were chosen in each city that were relatively the best representatives of the built-up area. The selected houses were then divided into live categories according to the house locations and building characteristics. CR-39 detectors, placed in polyethylene bags. were installed at head height in bedrooms and sitting rooms of all the selected houses and were exposed to radon and its daughter products for 90 days. Four such measurements were performed over a year in order to average out the seasonal variation in radon levels. After exposure, all the detectors were etched and counted under an optical microscope. The track densities of four measurements were averaged out and related to radon concentration levels. The radon levels were found to be 20, 20, 26, 28, 34, 42, 47 Bq m(-3) in the bedrooms and 24, 26, 27, 26, 37, 40, 43 Bq m(-3) in sitting rooms of Hasilpur, Rahimyar Khan, Minchin Abad, Fort Abbas, Sadiq Abad, Bahawalpur and Liaqatpur respectively. The observed variation in the radon level may be attributed to the geological variation in the area. Based on the observed data, excess lung cancer risk was assessed using the risk factors recommended by the USEPA, UNSCEAR and the ICRP. According to the EPA model, the lifetime excess lung cancer risk due to the lifetime exposure is found to vary from 12-102 per million per year in the houses surveyed. This variation is from 16-114 and 26-62 per million per year if UNSCEAR and ICRP limits are applied respectively.     

Biosynthesized Gold Nanoclusters and Iron Complexes as Scaffolds for Multimodal Cancer Bioimaging

Cancer treatment has a far greater chance of success if the neoplasm is diagnosed before the onset of metastasis to vital organs. Hence, cancer early diagnosis is extremely important and remains a major challenge in modern therapeutics. In this contribution, facile and new method for rapid multimodal tumor bioimaging is reported by using biosynthesized iron complexes and gold nanoclusters via simple introduction of AuCl₄ ^? and Fe²⁺ ions. The observations demonstrate that the biosynthesized Au nanoclusters may act as fluorescent and computed tomography probes for cancer bioimaging while the iron complexes behave as effective contrast agent for magnetic resonance imaging. The biosynthesized iron complexes and gold nanoclusters are found biocompatible in vitro (MTT (3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide) assay) and in vivo for all the vital organs of circulatory and excretory system. These observations raise the possibility that the biosynthesized probes may find applications in future clinical diagnosis for deep seated early neoplasms by multimodal imaging.     

A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

Evolving Recurrent Neural Network using Cartesian Genetic Programming to Predict The Trend in Foreign Currency Exchange Rates

Forecasting the foreign exchange rate is an uphill task. Numerous methods have been used over the years to develop an efficient and reliable network for forecasting the foreign exchange rate. This study utilizes recurrent neural networks (RNNs) for forecasting the foreign currency exchange rates. Cartesian genetic programming (CGP) is used for evolving the artificial neural network (ANN) to produce the prediction model. RNNs that are evolved through CGP have shown great promise in time series forecasting. The proposed approach utilizes the trends present in the historical data for its training purpose. Thirteen different currencies along with the trade-weighted index (TWI) and special drawing rights (SDR) is used for the performance analysis of recurrent Cartesian genetic programming-based artificial neural networks (RCGPANN) in comparison with various other prediction models proposed to date. The experimental results show that RCGPANN is not only capable of obtaining an accurate but also a computationally efficient prediction model for the foreign currency exchange rates. The results demonstrated a prediction accuracy of 98.872 percent (using 6 neurons only) for a single-day prediction in advance and, on average, 92% for predicting a 1000 days’ exchange rate in advance based on ten days of data history. The results prove RCGPANN to be the ultimate choice for any time series data prediction, and its capabilities can be explored in a range of other fields.