Input-Output Structure of Marginal and Small Farmers - An Analysis

Agriculture is the mainstay of the Indian economy. Agriculture and allied sectors, contribute nearly 22 per cent of Gross Domestic Product (GDP of India). About 65-70 per cent of the population is dependent on agriculture for their livelihood. An attempt had been made to study the characteristics of sample agricultural farmers, labour utilisation and input and output structure for marginal and small farmers cultivating cereals and pulses in Tuticorin District of Tamilnadu. Multistage stratified random sampling technique has been adopted for the study. Out of 300 sample farmer's cultivations cereals and pulses, 150 sample farms are under the category of cereals and remaining 150 sample farms come under pulses. The data relates to the month of November 2011. It may be concluded from the analysis that as in the case of cereals, the marginal farmers were efficient in the use of inputs like fertilizers and pesticides and marginal farmers have produced more yields per acre than small farmers and farmer groups of pulses. Key words: agriculture, cereals and pulses, small and marginal farmers, labour utilisation, Z-test

Socio-Economic Impact through Self Help Groups

The overall objective of the present study is to analysis the economic empowerment of women though SHGs in three villages of Tuticorin District of Tamilnadu.  This study is compiled with the help of the primary data covered only in a six month period (2011).  Totally 238 respondents were selected from 18 SHGs of three villages by using simple random sampling method.  Empowerment signifies increased participation in decision-making and it is this process through which people feel themselves to be capable of making decisions and the right to do so. Women’s participation in decision-making in family is important indicator for measuring their empowerment. The analysis shows that 66 percent beneficiaries reported decisions are being taken by their husbands, yet, more than 34 percent respondents accepted that they do participate in decision-making process. Thus, the socio-economic conditions of women have demonstrated that their status has improved since the joining of SHG’s and availing microfinance. The result of chi-square- test revealed that there is significant difference between participation in decision-making in family and SHG women members in Tuticorin District. Keywords: Self-Help Groups, women empowerment, percentage analysis, averages, chi-square test

Design Approach to Implementation Of Arbitration Algorithm In Shared Bus Architectures (MPSoC)

The multiprocessor SoC designs have more than one processor and huge memory on the same chip. SoC consists of hardware cores and software cores ,multiple processors, embedded DRAM and connectors between cores .A wide range of MPSOC architectures have been developed over the past decade. This paper surveys the history of various On-Chip communication architectures present in the design of MPSoC. This acts as a primary factor of overall performance in complex SoC designs. Some of the various techniques that have driven the design of MpSoC has been discussed. Dynamically configurable communication architectures are found to improve the system performance. Currently On-chip interconnection networks are mostly implemented using shared buses which are the most common medium. The arbitration plays a crucial role in determining performance of bus-based system, as it assigns priorities, with which processor is granted the access to the shared communication resources. In the conventional arbitration algorithms there are some drawbacks such as bus starvation problem and low system performance. The bus should provide each component a flexible and utmost share of on-chip communication bandwidth and should improve the latency in access of the shared bus. The performance of SoC is improved using the probabilistic round robin algorithm with regard to the parameters, latency.Thus in this paper various issues related to bus arbitration related to design of MPSoC is analysed

Energy efficient decision fusion for differential space-time block codes in wireless sensor networks

The non-coherent techniques that do not require the channel state information have gained significant interest especially when multiple transmitter and receiver nodes are involved in communication. In this paper, we analyze the energy efficiency of differential and coherent cooperative Multiple-input Multiple-output (MIMO) method using space-time block codes (STBC). We exploit the benefits of the extension of the observation interval of differential STBC to three blocks in Wireless sensor networks (WSNs). We propose an energy efficient decision fusion (EEDF) algorithm in WSNs which utilizes the benefits of Multiple symbol differential detection (MSDD) decision fusion by optimally selecting the ring amplitude of the differential amplitude phase shift keying (DAPSK) constellation. The simulation results show that processing differential multiple symbols provides significant energy saving compared to the conventional two-symbol processing. Furthermore, significant performance gain is achieved for the proposed algorithm compared to 16 DPSK MSDD decision fusions

A Progressive UNDML Framework Model for Breast Cancer Diagnosis and Classification

According to recent research, it is studied that the second most common cause of death for women worldwide is breast cancer. Since it can be incredibly difficult to determine the true cause of breast cancer, early diagnosis is crucial to lowering the disease\u27s fatality rate.  Early cancer detection raises the chance of survival by up to 8 %. Radiologists look for irregularities in breast images collected from mammograms, X-rays, or MRI scans. Radiologists of all levels struggle to identify features like lumps, masses, and micro-calcifications, which leads to high false-positive and false-negative rates. Recent developments in deep learning and image processing give rise to some optimism for the creation of improved applications for the early diagnosis of breast cancer. A methodological study was carried out in which a new Deep U-Net Segmentation based Convolutional Neural Network, named UNDML framework is developed for identifying and categorizing breast anomalies. This framework involves the operations of preprocessing, quality enhancement, feature extraction, segmentation, and classification. Preprocessing is carried out in this case to enhance the quality of the breast picture input. Consequently, the Deep U-net segmentation methodology is applied to accurately segment the breast image for improving the cancer detection rate. Finally, the CNN mechanism is utilized to categorize the class of breast cancer. To validate the performance of this method, an extensive simulation and comparative analysis have been performed in this work. The obtained results demonstrate that the UNDML mechanism outperforms the other models with increased tumor detection rate and accurac

Energy efficient decision fusion for differential space-time block codes in wireless sensor networks

147-156The non-coherent techniques that do not require the channel state information have gained significant interest especially when multiple transmitter and receiver nodes are involved in communication. In this paper, we analyze the energy efficiency of differential and coherent cooperative Multiple-input Multiple-output (MIMO) method using space-time block codes (STBC). We exploit the benefits of the extension of the observation interval of differential STBC to three blocks in Wireless sensor networks (WSNs). We propose an energy efficient decision fusion (EEDF) algorithm in WSNs which utilizes the benefits of Multiple symbol differential detection (MSDD) decision fusion by optimally selecting the ring amplitude of the differential amplitude phase shift keying (DAPSK) constellation. The simulation results show that processing differential multiple symbols provides significant energy saving compared to the conventional two-symbol processing. Furthermore, significant performance gain is achieved for the proposed algorithm compared to 16 DPSK MSDD decision fusions

Phytotherapeutic control of food borne pathogens by Jasminum sambac L. flowers

Objective: This study is aimed to determine the antibacterial effect of Jasminum sambac against foodborne pathogens.Methods: Antibacterial activity of methanol and chloroform extract of J. sambac flowers against foodborne pathogens (Bacillus cereus, Listeria monocytogenes, Shigella flexeneri, Salmonella serovar enterica Typhi, Staphylococcus aureus and Escherichia coli) were performed using disc diffusion method and their minimal inhibitory concentration (MIC) was also determined. The preliminary phytochemical screening and gas chromatography-mass spectroscopic (GC-MS) analysis of methanol and chloroform extract of J. sambac was analyzed using GC Clarus 500 Perkin Elmer System and gas chromatograph interfaced with a mass spectrometer.Results: Phytochemical and GC-MS studies revealed the presence of bioactive compounds and found to possess antibacterial activity against foodborne pathogens.Conclusion: The present study supports the possible use of these phytotherapeutic agents in the clinical management of foodborne diseases.Keywords: GC-MS analysis, Foodborne pathogens, Jasminum sambac L., Antibacterial activit

Cytosolic Fe-S cluster protein maturation and iron regulation are independent of the mitochondrial Erv1/Mia40 import system

The sulfhydryl oxidase Erv1 partners with the oxidoreductase Mia40 to import cysteine-rich proteins in the mitochondrial intermembrane space. In Saccharomyces cerevisiae, Erv1 has also been implicated in cytosolic Fe-S protein maturation and iron regulation. To investigate the connection between Erv1/Mia40-dependent mitochondrial protein import and cytosolic Fe-S cluster assembly, we measured Mia40 oxidation and Fe-S enzyme activities in several erv1 and mia40 mutants. Although all the erv1 and mia40 mutants exhibited defects in Mia40 oxidation, only one erv1 mutant strain (erv1-1) had significantly decreased activities of cytosolic Fe-S enzymes. Further analysis of erv1-1 revealed that it had strongly decreased glutathione (GSH) levels, caused by an additional mutation in the gene encoding the glutathione biosynthesis enzyme glutamate cysteine ligase (GSH1). To address whether Erv1 or Mia40 plays a role in iron regulation, we measured iron-dependent expression of Aft1/2-regulated genes and mitochondrial iron accumulation in erv1 and mia40 strains. The only strain to exhibit iron misregulation is the GSH-deficient erv1-1 strain, which is rescued with addition of GSH. Together, these results confirm that GSH is critical for cytosolic Fe-S protein biogenesis and iron regulation, whereas ruling out significant roles for Erv1 or Mia40 in these pathways