Design of artificial neuron controller for STATCOM in dSPACE environment

Reactive power compensation is an important issue in the control of electric power system. Reactive power from the source increases the transmission losses and reduces the power transmission capability of the transmission lines. Moreover, reactive power should not be transmitted through the transmission line to a longer distance. Hence Flexible AC Transmission Systems (FACTS) devices such as static compensator (STATCOM) unified power flow controller (UPFC) and static volt–ampere compensator (SVC) are used to alleviate these problems. In this paper, a voltage source converter (VSC) based STATCOM is developed with PI and Artificial Neural Network Controller (ANNC). The conventional PI controller has more tuning difficulties while the system parameter changes, whereas a trained neural network requires less computation time. The ANNC has the ability to generalize and can interpolate in between the training data. The ANNC designed was tested on a 75 V, ±3KVAR STATCOM in real time environment via state-of-the-art of digital signal processor advanced control engineering (dSPACE) DS1104 board and it was found that it was producing better results than the PI controller.     

Aluminum nitride by microwave-assisted synthesis: Effect of added ammonium chloride

Hexagonal aluminum nitride (AlN) crystals were synthesized by microwave method with ammonium chloride used as an additive. Starting mixtures consisted of Al powder, NH₄Cl, and urea as a fuel taken in a 1: 3: 1 ratio. The microwave oven operated at 630 W, the synthesis time was 10, 30, 60, and 120 min. The results showed that the pure AlN powder with regular and fine grains could be obtained in 30 min. The synthesized powders were characterized by TGA/DTA, XRD, FT-IR, UV-VIS, SEM, and TEM.     

Correction of post burns contracture of wrist with Ilizarov method

A case of severe post burns contracture of the wrist, of 43 years duration resulting in recurrent ulceration of the skin was successfully treated by gradual distraction using the Ilizarov method. This method is superior to plaster of Paris cast and is more versatile than other forms of external fixation.     

Color determinants of surface stratification

Although color plays a crucial role in the demarcation of surfaces in the visual field, its role in depth perception is not well understood. Certain special effects of color on depth perception that arise from optical factors such as chromatic aberration (chromostereopsis) have been studied, but less is known about the role of perceptual factors of color in determining depth relations. The present study explores the role that the different attributes of color such as hue, chroma, and lightness play in the stratification of surfaces in depth. In two experiments, subjects manipulated specific dimensions of colors (hue, chroma, lightness, and whiteness) while making judgments of coplanarity of either two or more abutting surfaces. The results demonstrate that for surfaces to appear coplanar, their lightness has to be proportional to the natural (intrinsic) lightness of the hues. No meaningful effects of chroma, whiteness, or blackness were found in depth stratification. The results suggest a primary role of the natural lightness of hues in depth perception.     

Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

Abstract

Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R² value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.     

CORROSION INHIBITION OF CARBON STEEL IN LOW CHLORIDE MEDIA BY AN AQUEOUS EXTRACT OF HIBISCUS ROSA-SINENSIS LINN

The inhibition efficiency (IE) of an aqueous extract of white flower, namely, Hibiscus rosa-sinensis Linn., in controlling corrosion of carbon steel immersed in an aqueous solution containing 60 ppm of Cl^-has been evaluated by the mass loss method. The flower extract (FE) shows good IE. In the presence of Zn²⁺, excellent IE is shown by the flower extract. A synergistic effect exists between the flower extract and Zn²⁺. The mechanistic aspects of corrosion inhibition have been investigated by polarization study and AC impedance spectra. Polarization study reveals that the formulation consisting of flower extract and Zn²⁺ functions as a mixed inhibitor. AC impedance spectra reveal that a protective film is formed on the metal surface. The active principle in the flower extract is quercetin-3-O-glucoside. This has been confirmed by UV-visible absorption spectra. The protective film formed on the metal surface has been analyzed by FT-IR and AFM spectra. It is found that the protective film consists of Fe²⁺-quercetin-3-O-glucoside complex and Zn(OH)₂.     

Salient object based visual sentiment analysis by combining deep features and handcrafted features

Multimedia Tools and Applications - With the rapid growth of social networks, the visual sentiment analysis has quickly emerged for opinion mining. Recent study reveals that the sentiments conveyed...     

Hospital-made diet versus commercial supplement in postburn nutritional support

Nutritional support is an important aspect of the management of burn patients. Nutrition supplementation can be achieved either by 'hospital-made' or 'commercial' diets. Commercial diets are efficacious but expensive and sometimes not easily available. This study was undertaken to compare the efficacy and tolerance of a hospital-made diet with a commercial diet. Twenty patients with burns ranging from 20-50 per cent TBSA were studied to compare the efficacy and tolerance of the 'hospital-made' diet with 'commercial' preparations. Patients were divided into two groups of 10 each and randomised within each group to receive either a hospital-made diet (five patients) or a commercial diet (five patients). Efficacy of diet was assessed by evaluation of nutritional status, graft take, number of surgical procedures and duration of hospital stay. Tolerance was assessed by recording side effects such as nausea, vomiting, abdominal distention and diarrhoea. Both diets were well tolerated by all patients. There was no significant difference in nutritional status, number of surgical procedures, percentage of graft take and duration of hospital stay on either diet, suggesting that hospital-made diets are similar in efficacy and tolerance but cheaper and more easily available. They are a good alternative to 'commercial' diets, especially in poor patients.     

A Comparison of the Performance Indices of Embedded EZ-Source Inverter Using Different PWM Techniques

Wireless Personal Communications - Many converters were proposed for boost/buck operation for power supply. But these converters have more stages due to separate boost or buck converters, as a...     

Investigating the performance of Hadoop and Spark platforms on machine learning algorithms

One of the most challenging issues in the big data research area is the inability to process a large volume of information in a reasonable time. Hadoop and Spark are two frameworks for distributed data processing. Hadoop is a very popular and general platform for big data processing. Because of the in-memory programming model, Spark as an open-source framework is suitable for processing iterative algorithms. In this paper, Hadoop and Spark frameworks, the big data processing platforms, are evaluated and compared in terms of runtime, memory and network usage, and central processor efficiency. Hence, the K-nearest neighbor (KNN) algorithm is implemented on datasets with different sizes within both Hadoop and Spark frameworks. The results show that the runtime of the KNN algorithm implemented on Spark is 4 to 4.5 times faster than Hadoop. Evaluations show that Hadoop uses more sources, including central processor and network. It is concluded that the CPU in Spark is more effective than Hadoop. On the other hand, the memory usage in Hadoop is less than Spark.