33 research outputs found
Dimensionality Reduction of Hyperspectral Imagery Using Random Projections
Hyperspectral imagery is often associated with high storage and transmission costs. Dimensionality reduction aims to reduce the time and space complexity of hyperspectral imagery by projecting data into a low-dimensional space such that all the important information in the data is preserved. Dimensionality-reduction methods based on transforms are widely used and give a data-dependent representation that is unfortunately costly to compute. Recently, there has been a growing interest in data-independent representations for dimensionality reduction; of particular prominence are random projections which are attractive due to their computational efficiency and simplicity of implementation. This dissertation concentrates on exploring the realm of computationally fast and efficient random projections by considering projections based on a random Hadamard matrix. These Hadamard-based projections are offered as an alternative to more widely used random projections based on dense Gaussian matrices. Such Hadamard matrices are then coupled with a fast singular value decomposition in order to implement a two-stage dimensionality reduction that marries the computational benefits of the data-independent random projection to the structure-capturing capability of the data-dependent singular value transform. Finally, random projections are applied in conjunction with nonnegative least squares to provide a computationally lightweight methodology for the well-known spectral-unmixing problem. Overall, it is seen that random projections offer a computationally efficient framework for dimensionality reduction that permits hyperspectral-analysis tasks such as unmixing and classification to be conducted in a lower-dimensional space without sacrificing analysis performance while reducing computational costs significantly
Distress debt and suicides among agrarian households : findings from three village studies in Kerala
This paper examines the factors and process underlying agrarian
distress in Kerala by undertaking the case studies of three villages situated
in Wayanad and Idukki districts namely, Cherumad, Kappikkunnu and
Upputhara. The impact of distress on household livelihoods and
indebtedness and how they cope up with the situation are examined with
entire village and intra village analysis of data. The process of agrarian
distress which resulted in suicides were analysed through a few in-depth
studies.
Decline in crops yield, coupled with sharp fall in their prices,
created severe distress in all sections of agricultural population. Many
household cope with these distresses by reducing household expenditure,
diversifying their household incomes and searching for jobs in other
places. Meanwhile, government interventions in terms of PDS, health
care provision, education and supply of drinking water gave some relief
to the affected persons. However, these measures could not completely
prevent the occurrence of suicides among the members of agrarian
households. The paper shows that the villages in which household income
are more diversified and social networks much stronger, the distress
conditions did not result in suicides. Mitigation of agrarian distress
requires not only for debt relief but also implementation of long term
strategies containing policies to promote price stability, ecological
sustainability of agriculture, strengthening of formal rural credit and
support networks, and income and employment generation programmes.
Key words: Distress debt, Suicides, Agrarian Households, Livelihood
risk, Coping Strategies, Livelihood, Livelihood Assets,
Institutions, Kerala
JEL Classification: Q, Q0
Lease farming in Kerala : findings from micro level studies
Land Reforms Act in Kerala rendered tenancy invalid and
prohibited the creation of future tenancies in the State, but tenancy very
much exists. It is a consequence of the simultaneous increase in two
categories of people, “those who have land but unable to cultivate’ and
‘those who have the labour and skills, but no lands or not enough lands
of their own to cultivate’. Macro state-level data on tenancy from sources
such as the NSS appear to be gross under-estimations, going by the data
provided by micro-level studies in the state. This paper examines some
micro-level studies on tenancy in Kerala, more specifically, its prevalence
across locations and crops, characteristics of lessors and lessees, the terms
of lease, and the income derived from lease cultivation and in the light
of the analysis, argues for institutionalised arrangements for the expansion
of lease cultivation, rather than sterner measures to check it. Among
other factors, large-scale entry of self-help groups into the lease market
to take up lease cultivation, often bringing hitherto fallowed lands into
production, has prompted such a positioning.
Key Words: Lease farming, Commercial Cultivation, Sustainable
Agriculture
JEL Classification: Q10, Q1
Livelihood risks and coping strategies : a case study in the agrarian village of Cherumad, Kerala
This paper examines the various dimensions of livelihood risk as
informed by a in-depth case study of an agrarian village namely,
Cherumad in Kerala. The livelihood risk in Cherumad since the last
quarter of the 1990’s has been unique and unprecedented in their nature
and intensity. The effect of price risk and productivity risk of crops
became an income risk to the farming community. For agricultural labour
too it was an income risk with double effects of wage risk and employment
risk. These risk have resulted in a general fall in the living standards of
people.
The livelihood dynamics in Cherumad shows that improvement
in livelihood assets improves livelihood outcomes and vice versa.
Institutions (both formal and informal) affect access to assets and
livelihood outcomes. Across socio-economic groups, livelihood outcome
are determined by the portfolio of livelihood assets, especially land. The
households have developed a number of coping strategies in response to
distress. These strategies are meant to smooth consumption and income
and rebuilding household livelihood. In this context, the overall emphasis
of state intervention should be in strengthening their livelihood assets.
Key words: Livelihood risk, Coping Strategies, Livelihood, Livelihood
Assets, Institutions, Kerala
JEL Classification: Q, Q 00
NEVIRAPINE INDUCED STEVENS JOHNSON SYNDROME: A CASE REPORT
Adverse drug reactions (ADRs) are one of the major reasons for morbidity and mortality in India, but they often go undetected and under reported. Nevirapine (NVP) is one of the first line agents used for anti retroviral treatment (ART) of human immunodeficiency virus (HIV) infection. It is known to cause mild skin rash among these individuals during the first weeks of therapy, however Stevens Johnsons Syndrome (SJS) is rare. Here we report afifty three-year-old HIV positive individual presenting with maculopapular rash all over the body and ulcerations of the oral and genital mucosa following administration of NVP. He was diagnosed to have SJS. The symptoms resolved completely 2 weeks after stopping the drug. Causality assessment using Naranjo and the World Health Organisation (WHO) probability scale indicated a probable relationship between the patient's symptoms and the use of NVP. Thus, clinicians should be vigilant to allow early detection of these problems, as the early diagnosis and treatment of SJS can reduce the morbidity and mortality considerably.Â
Agrarian distress and livelihood strategies : a study in Pulpalli Panchayat, Wayanad District, Kerala
This paper examines the household livelihood strategies under
agrarian distress in Pulpalli Panchayat of Kerala. It also looks at the
relationship between household assets and livelihood strategies. The
negotiations of institutions by the marginalized and depressed sections
of the society were analysed in detail.
Major causes of agrarian distress in the study area are the ecological
degradation and fall in crops income. Land continues to be the most
important asset determining livelihood outcomes. The livelihood
strategies have been investigated in relation to land, education, housing
pattern, investments & credit facilities, and participation in organizational
activities. The livelihood strategies adopted by farmers in the wake of
agrarian crisis includes diversification of agriculture, share cropping,
organic farming, self-help group activities, cattle rearing, migration and
exchange of labour. Livelihood strategies varied across socio-economic
groups as farmers owning better landholdings diversified cropping
patterns while poor households participated in the activities of SHGs.
Casual agricultural labourers and marginal farmers moved to other places
in search of jobs. Mitigation of agrarian distress requires public provision
of education, health and other social safety measures.
Key words: Livelihood risk, Coping Strategies, Livelihood, Livelihood
Assets, Institutions, Wayanad, Kerala
JEL Classification: Q, Q 0
Adenosine deaminase as marker of insulin resistance
Background:Type-2 diabetes complications contribute to increased morbidity and mortality and hence early diagnosis and control of diabetes is necessary. Adenosine deaminase activity is present in almost all human tissues, but the highest levels are found in lymphoid system. Aim of the study was to identify the correlation between adenosine deaminase levels and insulin resistance in type-2 diabetics and serum adenosine deaminase levels and glycemic control.Methods: In this case control study, patients with type-2 diabetes mellitus, attending out-patient department or admitted in the hospital during the study period, fulfilling the study criteria were taken up.Results: 200 patients were included in the study, with 100 patients in the case and controls group respectively. The mean body mass index, waist circumference, fasting blood sugar, post prandial blood sugar, glycosylated hemoglobin, fasting serum insulin levels, quantitative insulin sensitivity check index values were found to be significantly elevated (p<0.0001) in case group compared to controls. Quantitative insulin sensitivity check index was significantly reduced (p<0.0001) in study group compared to controls. Adenosine deaminase levels were significantly high (p<0.0001) in the study group compared to the control group, with a mean value of 22.35 U/L against 4.38 U/L. Adenosine deaminase levels were found to have a linear association with elevated fasting blood sugar and post prandial blood sugar, with a statistical significance (p<0.0001).Conclusions: We identified that the highest Adenosine deaminase levels were detected in poorly controlled type-2 diabetes mellitus. Adenosine deaminase levels were found to have positive correlation with body mass index, fasting blood sugar and post prandial blood sugar levels. Adenosine deaminase levels were also positively correlated with insulin resistance, as calculated by homeostasis model assessment of insulin resistance. Adenosine deaminase levels were found to have an inversely proportional correlation with quantitative insulin sensitivity check index.
An Effective Transfer Learning Based Landmark Detection Framework For UAV-Based Aerial Imagery Of Urban Landscapes
Aerial imagery captured through airborne sensors mounted on Unmanned Aerial Vehicles (UAVs), aircrafts, satellites, etc. in the form of RGB, LiDAR, multispectral or hyperspectral images provide a unique perspective for a variety of applications. These sensors capture high-resolution images that can be used for applications related to mapping, surveying, and monitoring of crops, infrastructure, and natural resources. Deep learning based algorithms are often the forerunners in facilitating practical solutions for such data-centric applications. Deep learning-based landmark detection is one such application which involves the use of deep learning algorithms to accurately identify and locate landmarks of interest in images captured through UAVs. This study proposes an efficient transfer learning method for feature extraction using a ResNet50 architecture, paired with a FasterRCNN object detection for an automated landmark detection framework. Additionally, a novel technique for hierarchical image annotation and synthetic sampling is also introduced to address the issue of class imbalance. Empirical results prove that our proposed approach outperforms other state-of-the-art landmark detection methodologies compared