South-West Monsoon Rainfall of Kerala and Its Variability

This study focuses on the south –west monsoon rainfall over Kerala and its variability both on the spatial and temporal scales. The main objectives of the study are, interanual, long-term and decadal variabilities in MRF(monsoon rain fall),relationship between antecedent global circulation parameters, diurnal variability using data of a large number of stations in Kerala and the spatial distribution of rainfall under two large scale synoptic. Kerala gets nearly 190cm of rainfall during the south-west monsoon season 1st June to 30th September. This is more than twice the monsoon rainfall of India. A good part of kerala’s rainfall is caused by the orography of the Western Ghats Mountain ranges. The state receives 286cm of annual rainfall of which 68%is during the south-west monsoon season. The summer monsoon rainfall of Kerala shows a decreasing trend of 12.0%in 96 years. The study shows that the Intra Seasonal Oscillations(ISO) of the monsoon season has large interanual variability,some years having long period and other years having short period ISO. It is seen that Western Ghats has a strong control on the east west profile on the monsoon rainfall.

Dynamic characteristics of Atmospheric boundary Layer during different phases of Monsoon

Atmospheric Boundary layer (ABL) is the layer just above the earth surface and is influenced by the surface forcing within a short period of an hour or less. In this thesis, characteristics of the boundary layer over ocean, coastal and inland areas of the atmosphere, especially over the monsoon regime are thoroughly studied. The study of the coastal zone is important due to its high vulnerability mainly due to sea breeze circulation and associated changes in the atmospheric boundary layer. The major scientific problems addressed in this thesis are diurnal and seasonal variation of coastal meteorological properties, the characteristic difference in the ABL during active and weak monsoons, features of ABL over marine environment and the variation of the boundary layer structure over an inland station. The thesis describes the various features in the ABL associated with the active and weak monsoons and, the surface boundary layer properties associated with the active and weak epochs. The study provides knowledge on MABL and can be used as the estimated values of boundary layer parameters over the marine atmosphere and to know the values and variabilities of the ABL parameters such as surface wind, surface friction, drag coefficient, wind stress and wind stress curl.

Metabolic Efficiency of Penaeus Indicus H.Milne Edwards Under Different Salinity Stress Conditions

The investigation was aimed at establishing the effect of salinity on the culture performance of Peneus Indicus in pokkali fields and also to find out the growth performance of the shrimp at varying salinities. The experiments were laid out at Rice Research Station, Vyttila of Kerala Agriculture University in three fields of area 1000 m2 each. The results of the experiment clearly establish that shrimps when stocked at higher salinity (20-25 ppt) for 45 days has given higher growth, survival and production than those stocked at lower salinity (10-15 ppt) in all the above parameters even when the culture experiment was maintained for longer periods in lower salinity. In the prolonged culture experiments conducted for 120 days in 10-25 ppt salinity, the results were poorer than the short period culture in higher salinity and the production values similar to lower saline culture. This clearly establishes the importance of salinity as an ecological factor which will have profound influence in shrimp farming operations.

An agroclimatic assessment of the crop growth potential of south india

Usually, under rainfed conditions the growing period exists in the humid months. Hence, for agricultural planning knowledge about the variabilities of the duration of the humid seasons are very much needed. The crucial problem affecting agriculture is the persistency in receiving a specific amount of rainfall during a short period. Agricultural operations and decision making are highly dependent on the probability of receiving given amounts of rainfall; such periods should match the water requirements of different phenological phases of the crops. While prolonged dry periods during sensitive phases are detrimental to their growth and lower the yields, excess of rainfall causes soil erosion and loss of soil nutrients. These factors point to the importance of evaluation of wet and dry spells. In this study the weekly rainfall data have been analysed to estimate the probability of wet and dry periods at all selected stations of each agroclimatic zone and the crop growth potentials of the growing seasons have been analysed. The thesis consists of six Chapters.

Fenneropenaeus indicus is protected from white spot disease by oral administration of inactivated white spot syndrome virus

Fenneropenaeus indicus could be protected from white spot disease (WSD) caused by white spot syndrome virus (WSSV) using a formalin-inactivated viral preparation (IVP) derived from WSSV-infected shrimp tissue. The lowest test quantity of lyophilized IVP coated onto feed at 0.025 g–1 (dry weight) and administered at a rate of 0.035 g feed g–1 body weight d–1 for 7 consecutive days was sufficient to provide protection from WSD for a short period (10 d after cessation of IVP administration). Shrimp that survived challenges on the 5th and 10th days after cessation of IVP administration survived repeated challenges although they were sometimes positive for the presence of WSSV by a polymerase chain reaction (PCR) assay specific for WSSV. These results suggest that F. indicus can be protected from WSD by simple oral administration of IVP

THE CONCEPT OF SEX IN HINDI SHORT STORIES OF THE POST—PREMCHAND PERIOD 1935-60

HINDI

Impact of Monetary Policy on Indian Economy in the Post-Reform Period

The present study was an attempt to analyze systematically the techniques of monetary control measures with its relevance and changing importance and to find out their effectiveness in the Indian context especially to achieve the thriving objectives of price stability and economic growth.There is definite and remarkable economic impact of monetary policy on Indian economy in the post-reform period. The importance of monetary policy has been increasing year after year. Its role is very relevant in attaining monetary objectives, especially in managing price stability and achieving economic growth. Along that, the use and importance of monetary weapons like Bank rate, CRR, SLR, Repo rate and Reverse Rate have increased over the years. Repo and Reverse Repo rates are the most frequently used monetary techniques in recent years. The rates are varied mainly for curtailing inflation and absorb the excess liquidity and hence to maintain price stability in the economy. Thus, this short-time objective of price stability is more successful on Indian economy rather than other long-term objectives of development.Monetary policy rules can be active or passive. The passive rule is to keep the money supply constant, which is reminiscent of Milton Friedman’s money growth rule. The second, called a price stabilization rule, is to change the money supply in response to changes in aggregate supply or demand to keep the price level constant. The idea of an active rule is to keep the price level and hence inflation in check. In India, this rule dominates our monetary policy. A stable growth is healthy growth.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.