Stability of Lending Rate Stickiness: A Case Study of India

The paper postulates that in an environment of continuous financial reforms, the lending rate stickiness in an economy could be changing over the period. The financial reforms (of which deregulation of interest rates formed a major part) during the 1990s and the early 2000s and the changing role attributed to different policy rates during the reforms make India an interesting case study. The paper finds evidence of diminishing lending rate stickiness in case of India. During the major part of the study, Indian policymakers used the discount rate for policy signaling. The paper observes that as a result, the long-term rates like the lending rates did not react sufficiently to the changes in the short-term rates (e.g., repo rate) in this period unless the discount rate was also changed. Such behavior changed when policymakers started to use short-term rates like repo rates for policy signaling. Results in this paper suggest that when the impacts are added together, a change of 100 basis points in all policy rates towards the end of the reference period could change the lending rate in India almost by similar magnitude. These findings help to reconcile some of the contrasting findings on lending rate stickiness in case of India. Among possible factors still responsible for lending rate stickiness, the study identifies inelastic credit demand in India as an important factor. From policymaking perspective, however, it is postulated that as demand for personal and housing loans in India are likely to increase in future due to demographic factor, it is likely that such increase could tend to increase inflexibility in loan rates.Lending Rate Stickiness, Discount Rate Addiction, Monetary Policy Transmission

On recognition of gestures arising in flight deck officer (FDO) training

This thesis presents an on-line recognition machine RM for the continuous and isolated recognition of dynamic and static gestures that arise in Flight Deck Officer (FDO) training. This thesis considers 18 distinct and commonly used dynamic and static gestures of FDO. Tracker and computer vision based systems are used to acquire the gestures. The recognition machine is based on the generic pattern recognition framework. The gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of the gestures via dynamic programming and Markovian process. The algorithm predicts the correspond-ing index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. Having estimated Score, some heuristics are employed to control the declaration in the final stages. The recognition machine addresses general gesture recognition issues: to recognize real time and dynamic gesture, no starting/end point and inter-intra personal tem-poral and spatial variance. The first two issues and temporal variance are addressed by the proposed algorithm. The spatial invariance is addressed by introducing inde-pendent units to construct gesture models. An important aspect of the algorithm is that it provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. The algorithm has the additional advantage of providing timely feedback for training purposes. In this thesis, we consider isolated and continuous gestures. The performance of RM is evaluated using six datasets - artificial (W_TTest), hand motion (Yang, Perrotta), Gesture Panel and FDO (tracker, vision). The Hidden Markov Model (HMM) and Dynamic Time Warping (DTW) are used to compare RM's results. Various data analyses techniques are deployed to reveal the complexity and inter similarity of the datasets before experiments are conducted. In the isolated recogni-tion experiments, the recognition machine obtains comparable results with HMM and outperforms DTW. In the continuous experiments, RM surpasses HMM in terms of sentence and word recognition. In addition to these experiments, a multilayer per-ceptron neural network (MLPNN) is introduced for the prediction process of RM to validate modularity of RM. The overall conclusion of the thesis is that, RM achieves comparable results which are in agreement with HMM and DTW. Furthermore, the recognition machine pro-vides more reliable and accurate recognition in the case of missing and noisy data. The recognition machine addresses some common limitations of these algorithms and general temporal pattern recognition in the context of FDO training. The recognition algorithm is thus suited for on-line recognition.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Stability analysis of seed yield in coriander based on non-parametric methods

The present study consisted of evaluation of 42 genotypes in two environments –with full irrigations (called irrigated) and with half the number of normal irrigations (called drought) over three years. ANOVA has indicated significant influence of environments on the expression of seed yield. All types of interactions with genotypes were significant indicating non-linear response of genotypes to environments. Stability analysis indicated significant differences among the ranks of stability of the genotypes. Significant positive correlations were noted among the different non parametric statistics and between corrected and uncorrected seed yield. Similarly there was good correspondence between the scatters of the genotypes obtained with Si(1), Si(2), Si(3) as well as between the scatters of AMMI (mean vs IPCA 1). &nbsp

Improved Facilities and Methodologies for Regenerating Unadapted and Wild Groundnut Germplasm at ICRISAT Genebank

Germplasm seed accessions require frequent regeneration for continued conservation and utilization. Regeneration of diverse crop germplasm accessions is a challenging task for large genebanks. The problem is severe especially with the wild relatives because of adaptation problems, lack of facilities and seasonal constraints where genebanks are located. Special facilities were created at ICRISAT Genebank for regenerating all the seed producing wild species of genus Arachis and unadapted Arachis hypogaea accessions. A total of 304 accessions represented by 41 wild species and 290 accessions of six botanical varieties of cultivated groundnut were successfully regenerated using these facilities. Much of the problems encountered during field regeneration especially with the wild species were overcome. Regeneration was possible round the year with minimum operational interference. The seedling establishment, plant growth and pod yields per cycle were significantly higher in these facilities. Establishing such facilities by genebanks could be advantages in efficient regeneration of problem accessions on a long-run for conservation and continued availability of diverse germplasm for utilization in crop improvement programs

ONE STEP QUANTIFICATION ANALYTICAL METHOD AND CHARACTERIZATION OF VALSARTAN BY LC-MS

Objective: To develop precise LC-MS method for the estimation of valsartan impurities and perform validation as per ICH guidelines.Methods: Valsartan (VLN) and its degradation products were analyzed by reverse phase high-performance liquid chromatography (RP-HPLC) using mobile phase water: acetonitrile: glacial acetic acid: phosphate buffer in the ratio of 500:500:1:0.5 v/v/v/v at 225 nm using column nucleosil C18, 125 ×4.0 mm, 5 µm. VLN sample (VLN SPL) thus obtained an unknown major impurity (UIMP) of 0.5 % at 0.38 retention time ratio (RRt) and purity of VLN was found to be 98.70 % respectively.Results: Estimation of VLN SPL total unknown impurities was found to be 1.3% by RP-HPLC. In similarly by liquid chromatography mass spectroscopy (LC-MS) a typical chromatogram of valsartan (VLN) at Rt 9.03 min and UIMP at Rt 3.3 min were recorded at a total run time of 23 min. Assay of VLN SPL was validated as per international council for harmonization (ICH) guidelines. Average % recovery was found to be 100.04 % for VLN SPL.Conclusion: The proposed work clearly indicates that the method can be easily adapted for the routine one step estimation of VLN active pharmaceutical ingredient (API)