Determinants of Women's Participation in Self-Help Group (SHG)-Led Microfinance Programme in Tamil Nadu

Factors determining participation of women in microfinance programme in Tamil Nadu have been identified following the multi-stage purposive and random sampling technique and selecting Coimbatore and Ramanathapuram districts for the study. It has been observed that socially backward, landless and marginal farm households participate more in this programme. Possession of livestock and consumer goods by the member households has been found to deter the joining of group. However, the number of households having informal borrowings, especially from moneylenders has been recorded to be higher among the members before joining the group. Analysis of determinants of women’s participation in microfinance programme using probit model has revealed that the age of women and value of productive assets other than land have a significant negative influence on their participation. However, social backwardness, indebtedness and presence of other microcredit programmes in the same or nearby villages have a significant positive influence on women’s participation in this programme.Agricultural Finance,

Food Security and Efficacy of the Intervention Mechanism in India

Rice and wheat are the two major foodgrains in India and their level of production determines the country self-sufficient. Forecasts on cereals supply range from 250 to over 300 million tones in the country by the year 2020. Mere availability of foodgrains is not a sufficient condition to ensure food security but also necessary that the poor have sufficient means to purchase food. Poor economic access leads to food security and it has been checked by the government mechanism through the operation of Targeted Public Distribution System (TPDS) and foodgrains are distributed at subsidized prices to the people living Below Poverty Line (BPL). It is a safety net to more than 330 million poor and those nutritionally at risk and an important delivery channel with a network of half million Fair Price Shops (FPS) catering to the needs of 199 million of ration cardholders. Food subsidy amounting to Rs. 25,800 (approximately US$ 5,730 million) was allotted during the period 2004-05, which rose ten times in the past 15 years. Higher level of procurement, revising the Minimum Support Price (MSP), inventory cost for stocking foodgrains and a lower level of issue price together absorb huge subsidy. Monte Carlo Technique was used to examine the implications of several policy options by simulating the 2002-03 base scenario. Optimum or the normative level of procurement, improving offtake from Food Corporation of India (FCI) godowns, private participation, issuing food stamps and food credit cards are the possible options to improve the efficacy of the system and reduce the budgetary burden due to subsidy.Food Security, Targeted Public Distribution System, Fair Price Shops, Minimum Support Price, Monte Carlo Technique, Food Security and Poverty, J21, H4, H5, O2, Q18,

MODELING NITRATE CONCENTRATION IN GROUND WATER USING REGRESSION AND NEURAL NETWORKS

Nitrate concentration in ground water is a major problem in specific agricultural areas. Using regression and neural networks, this study models nitrate concentration in ground water as a function of iron concentration in ground water, season and distance of the well from a poultry house. Results from both techniques are comparable and show that the distance of the well from a poultry house has a significant effect on nitrate concentration in groundwater.Environmental Economics and Policy, Livestock Production/Industries,

PREDICTIVE TIME MODEL OF AN ANGLIA AUTOFLOW MECHANICAL CHICKEN CATCHING SYSTEM

In this project, a predictive time model was developed for an Anglia Autoflow mechanical chicken catching system. At the completion of poultry growout, hand labor is currently used to collect the birds from the house, although some integrators are beginning to incorporate mechanical catching equipment. Several regression models were investigated with the objective of predicting the time taken to catch the chicken. A regression model relating distance to total time (sum of packing time, catching time, movement to catching and movement to packing) provided the best performance. The model was based on data collected from poultry farms on the Delmarva Peninsula during a six-month period. Statistical Analysis System (SAS) and NeuroShell Easy Predictor were used to build the regression and neural network models respectively. Model adequacy was established by both visual inspection and statistical techniques. The models were validated with experimental results not incorporated into the initial model.Livestock Production/Industries,

Immunoprotective Effect of Seabuckthorn (Hippophae rhamnoides) and Glucomannan on T-2 Toxin-Induced Immunodepression in Poultry

The present investigation was undertaken to study the immunoprotective effect of seabuckthorn berries and glucomannan against T-2 toxin-induced immunodepression in 15-day-old chicks. T-2 toxin was produced in the laboratory by growing Fusarium sporotrichioides MTCC 2081 on wheat. T-2 toxin was fed to birds at 1 ppm level of the diet. The powdered seabuckthorn berries were added at 400 and 800 ppm levels, and glucomannan added at 1 g/kg of feed. All the treatments were continued up to 28 days. The immunoprotective effects of seabuckthorn and glucomannan were assessed by evaluating humoral immune reaction against NCD vaccine (haemagglutination test and immunoglobulin estimation), serum immunoglobulin levels, phagocytic index, and DTH reaction against DNFB between day 25 and day 28 of experiment. There was significant (P < .05) decrease in non-specific immunity in T-2 toxin-treated group as evidenced by a reduction in phagocytic index, DTH reaction, HI titer, and total serum Ig compared to the healthy control group. A significant increase (P < .05) in HI titer and total serum Ig was seen in seabuckthorn and glucomannan fed group. A significant (P < .05) increase in DTH reaction and non-specific immune response was seen in seabuckthorn and glucomannan fed birds. The present investigation revealed that the seabuckthorn alone protected the immunosuppressant action of T-2 toxin, but seabuckthorn and glucomannan in combination provided an additive protection against T-2 toxicity

Implementation of RFID in Arignar Anna Central Library, Bharathiar University, Coimbatore: A Case Study

The RFID (Radio Frequency Identification), a technology that uses radio waves to automatically identify items or individuals. The library started utilizing RFIDs system to supplant their electro-attractive and bar code system in the last part of the 1990s. This paper attempts to discover detailed information about the new implementation of RFID in Arignar Anna Central Library and focuses on a different component of the system and their standards. The AACL started using RFID in the year 2017 under the supervision of the University Librarian, for their regular activities like circulation, shelf management, stock verification shelf rectification, and theft detection, etc. It also explained the relevant cost of the different components and the approximate total cost after implementing the RFID system

Wheat Growth, Yield, and Yield Contributing Attributes as a Function of Nitrogen Levels

To evaluate the effect of different levels of nitrogen on growth and yield of wheat a field experiment was conducted in 2017-18 at research area of cereals and pulses section, Ayyub agricultural research institute, Faisalabad. Eight levels of nitrogen i.e. 0, 29, 58, 87, 116, 145, 174, 203 kg ha-1 were evaluated. Experiment was laid out under randomized complete block design (RCBD) with three replications with a net plot size of 10×5m. Data were recorded for growth and yield parameters like number of tillers, plant height, spiklets per spike, seeds per spike, biological yield, 1000 grain weight, grain yield and harvest index. Different levels of nitrogen significantly increased all the growth and yield parameters. Maximum number of tillers, highest plant height and biological yield was recorded from the treatment where nitrogen was applied @ 203 Kg ha-1 while 1000 grain yield, seeds per spike and grain yield was achieved highest from where nitrogen applied @ 145 Kg ha-1

Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring

The functionality of the Internet is continually changing from the Internet of Computers (IoC) to the “Internet of Things (IoT)”. Most connected systems, called Cyber-Physical Systems (CPS), are formed from the integration of numerous features such as humans and the physical environment, smart objects, and embedded devices and infrastructure. There are a few critical problems, such as security risks and ethical issues that could affect the IoT and CPS. When every piece of data and device is connected and obtainable on the network, hackers can obtain it and utilise it for different scams. In medical healthcare IoT-CPS, everyday medical and physical data of a patient may be gathered through wearable sensors. This paper proposes an AI-enabled IoT-CPS which doctors can utilise to discover diseases in patients based on AI. AI was created to find a few disorders such as Diabetes, Heart disease and Gait disturbances. Each disease has various symptoms among patients or elderly. Dataset is retrieved from the Kaggle repository to execute AI-enabled IoT-CPS technology. For the classification, AI-enabled IoT-CPS Algorithm is used to discover diseases. The experimental results demonstrate that compared with existing algorithms, the proposed AI-enabled IoT-CPS algorithm detects patient diseases and fall events in elderly more efficiently in terms of Accuracy, Precision, Recall and F-measure

A low-cost vision based navigation system for small size unmanned aerial vehicle applications

Not availabl