Technical Efficiency and its Determinants in Tomato Production in Karnataka, India: Data Envelopment Analysis (DEA) Approach

Low productivity in agriculture is mainly due to the inability of the farmers to exploit the available technologies fully, resulting in lower efficiencies of production. The present study has estimated the technical and scale efficiencies of tomato-producing farms in Karnataka, considering different production levels and has identified the determining factors of their technical efficiency. The study is based on the data collected from the major tomato-producing regions of Karnataka, viz. Kolar and Bangalore rural districts of Karnataka, under three-production situations, viz. small, medium and large farms. Data Envelopment analysis (DEA) and log linear regression models have been used for estimating the technical efficiency and its determining factors, respectively. The study has indicated that most of the farms irrespective of size of holding have shown technical inefficiency problems. The medium farmers have been observed with best measures of technical efficiency, which has been explained by factors such as the land and labour productivity and education. Though medium farmers have been found efficient, with higher yields, it is the small farmers who have emerged as price-efficient producers in terms of lower cost on production (Rs 1.72/kg compared to Rs 2.01 in medium farms and Rs 1.85 in large farms) and higher unit profit. Most of the farms have been observed to have potential to expand production and productivity, increasing technical efficiency as majority have been performing with increasing returns to scale.Agricultural and Food Policy,

Marketing Losses and Their Impact on Marketing Margins: A Case Study of Banana in Karnataka

The explicit evaluation of the post-harvest losses at different stages of marketing and their impact on farmers’ net price, marketing costs, margins and efficiency have been presented. It has been found that the existing methods tend to overstate the farmers’ net price and marketing margins of intermediaries. In fact, the margin of the retailers’ after taking into account the physical loss during retailing has been found to be negative (loss), which otherwise, was positive (profit) in the conventional estimation. Similarly, the producers’ net share and wholesalers’ margins also decrease substantially. It has been shown that marketing efficiency is inversely proportional to the marketing losses. The co-operative marketing has been found to be a more efficient system in terms of both operations and price. Marketing cost has been identified as the major constraint in the wholesale marketing channel and bringing down the costs, particularly the commission charges as demonstrated in the co-operative channel, will help in reducing the price-spread and increasing the producers’ margin. The need for specialized transport vehicles for perishable commodities has been highlighted.Crop Production/Industries, Marketing,

SCDT: FC-NNC-structured Complex Decision Technique for Gene Analysis Using Fuzzy Cluster based Nearest Neighbor Classifier

In many diseases classification an accurate gene analysis is needed, for which selection of most informative genes is very important and it require a technique of decision in complex context of ambiguity. The traditional methods include for selecting most significant gene includes some of the statistical analysis namely 2-Sample-T-test (2STT), Entropy, Signal to Noise Ratio (SNR). This paper evaluates gene selection and classification on the basis of accurate gene selection using structured complex decision technique (SCDT) and classifies it using fuzzy cluster based nearest neighborclassifier (FC-NNC). The effectiveness of the proposed SCDT and FC-NNC is evaluated for leave one out cross validation metric(LOOCV) along with sensitivity, specificity, precision and F1-score with four different classifiers namely 1) Radial Basis Function (RBF), 2) Multi-layer perception(MLP), 3) Feed Forward(FF) and 4) Support vector machine(SVM) for three different datasets of DLBCL, Leukemia and Prostate tumor. The proposed SCDT &FC-NNC exhibits superior result for being considered more accurate decision mechanism

Novel modelling of clustering for enhanced classification performance on gene expression data

Gene expression data is popularized for its capability to disclose various disease conditions. However, the conventional procedure to extract gene expression data itself incorporates various artifacts that offer challenges in diagnosis a complex disease indication and classification like cancer. Review of existing research approaches indicates that classification approaches are few to proven to be standard with respect to higher accuracy and applicable to gene expression data apart from unaddresed problems of computational complexity. Therefore, the proposed manuscript introduces a novel and simplified model capable using Graph Fourier Transform, Eigen Value and vector for offering better classification performance considering case study of microarray database, which is one typical example of gene expression data. The study outcome shows that proposed system offers comparatively better accuracy and reduced computational complexity with the existing clustering approaches

A Study on Emerging Trends and Challenges in Mobile Cloud Computing

The proficiencies of mobile devices and mobile application continues to improve swiftly in relation to speed, computing power, storage and real world user friendly applications. Survey carried out by the Gartner Company (Famous global analytical consulting company) predicted more users to access the internet from the mobile devices than from the PCs by the year 2013. The outburst of the development in smart phones, applications and cloud computing concept has introduced Mobile Cloud Computing (MCC) as a dynamic technology for mobile devices. Mobile Cloud Computing (MCC) incorporates cloud computing into the mobile environment and overcome some problems in performance (e.g., battery life, storage), environment (e.g., scalability, availability) and security (reliability and privacy).Since MCC is still at primary stage of development we have to first theoretically understand the technology which would later on help us in the prediction of future research. In this paper, we introduce the background and theory of Mobile Cloud Computing (MCC), the benefits of MCC, challenges faced in MCC and finally some proposed possible future solution

Histopathological Image Classification Methods and Techniques in Deep Learning Field

A cancerous tumour in a woman's breast, Histopathology detects breast cancer. Histopathological images are a hotspot for medical study since they are difficult to judge manually. In addition to helping doctors identify and treat patients, this image classification can boost patient survival. This research addresses the merits and downsides of deep learning methods for histopathology imaging of breast cancer. The study's histopathology image classification and future directions are reviewed. Automatic histopathological image analysis often uses complete supervised learning where we can feed the labeled dataset to model for the classification. The research methods are frequentlytrust on feature extraction techniques tailored to specific challenges, such as texture, spatial, graph-based, and morphological features. Many deep learning models are also created for picture classification. There are various deep learning methods for classifying histopathology images

A retrospective study on ectopic pregnancy: a two year study

Background: Diagnosis of ectopic pregnancy was frequently missed and rising trend in incidence of ectopic pregnancies necessitates awareness about risk factors, resultant morbidity and mortality. Aim of the study was to determine the incidence, clinical presentation, risk factors, treatment and morbidity and mortality associated with ectopic pregnancy.Methods: Retrospective analysis of ectopic pregnancy was done in Government Raja Mirasudhar Hospital from January 2014 to December 2015. The following parameters: age, parity, gestational age, risk factors, clinical presentation, site of ectopic, diagnostic methods, mode of treatment and morbidity were noted.Results: Out of 27881 deliveries, 228 were ectopic pregnancies (0.81 %).Women with age 20-25yrs had highest incidence (42.98%) and with least below 20yrs (9.64%). Ectopic pregnancies were common in multiparous women than primigravida (18.42%). Common symptoms: abdominal pain (82.4%), amennorhea (78.5%), bleeding per vaginum (63.3%), asymptomatic (12%) patients. Urine pregnancy test positive in 90.4%. Etiology was pelvic infection (15.78%), infertility (7.01%), previous ectopic (8.33%), contraception (6.14), surgeries including LSCS and tubal surgeries (6.57%). Right sided ectopic was more common. Site of ectopic: Common in fallopian tube- ampullary region (63.15%), cornua (13.15%), isthmus (11.40%), fimbria (7.01%), followed by ovarian ectopic (3.94%) then cervical, caesarean scar, rudimentary horn pregnancy with 0.43% each. About 66.66% of ectopic was ruptured, 3/4th of these patients presented with shock at the time of presentation. Tubal abortions were seen in 20.17% of patients. Most of cases being ruptured ectopic pregnancies, salpingectomy in 90.52% and salpingoopherectomy in 3.5%. Morbidity was blood transfusion (76.31%), wound complications 4.38 and no mortality.Conclusions: Early diagnosis, identifying of underlying risk factors and timely intervention in the form of conservative or surgical treatment will help in reducing the morbidity and mortality associated with ectopic pregnancy.

IDENTIFICATION OF BIOACTIVE COMPOUNDS BY GAS CHROMATOGRAPHY-MASS SPECTROMETRY ANALYSIS OF SYZYGIUM JAMBOS (L.) COLLECTED FROM WESTERN GHATS REGION COIMBATORE, TAMIL NADU

Objective: The aim of this study was to investigate the presence of bioactive compounds in the methanolic leaf extract of Syzygium jambos.Methods: Collected leaves were shade dried and made into fine powder, extracted with methanol, and the methanolic extract was prepared and analyzed for the presence of bioactive compounds by gas chromatography-mass spectrometry (GC-MS). The mass spectrum of the chromatography was matched with NIST and WILEY Libraries.Results: The GC-MS analysis revealed the presence of 45 active compounds in the extract. From the GC-MS investigation, 1-Deoxy-d-mannitol3-methyl-2-methylsulfanyl-5-nitro-6-pyridin-4-ylpyrimidin-4-one, 3-Pentadecylphenol, 2-biphenylene carboxylic acid, Quinoline-3-carboxylic acid, and Stigmast-5-en-3-ol are important phytoconstituents which have antipyretic and antiparasitic activities.Conclusion: The present investigation revealed preliminary information on phytocompounds presented in S. jambos leaf extract which is very useful for the human community.Keywords: Syzygium jambos, Gas chromatography-mass spectrometry analysis, 1-Deoxy-d-mannitol, Phytoconstituents, Methanolic leaf extrac

Study of Oligohydramnios and its perinatal outcome

Background: Importance of amniotic fluid volume as an indicator of fetal status is being appreciated relatively recently. Around 3% to 8% of pregnant women are presenting with low amniotic fluid at any point of pregnancy. The present study was undertaken to study the outcome of pregnancies with Oligohydramnios [(amniotic fluid index) AFI≤5cm] at or beyond 34 weeks.Methods: This study consists of 50 cases of antenatal patients with oligohydramnios (AFI≤5) at or beyond 34 weeks of gestation compared with age and gestation matched 50 normal liquor (AFI≥5 and ≤25). The outcome measures recorded were labor, gestational age at delivery, amniotic fluid index (AFI), mode of delivery, indication for cesarean section or instrumental delivery, APGAR score and birth weight.Results: In the present study, AFI was significantly decreased in cases (3.74±1.2) compared (12.54±2.5) with controls. Variable deceleration was noted in 14 (28%) and late deceleration in 5 (10%) cases. In control group, 2 (4%) had late deceleration. In cases induced labor is in 14 (28%), spontaneous labor 36 (72%). In cases, term normal vaginal delivery was in 15 (30%), PVD in 6 (12%), LSCS in 28 (56%) and instrumental vaginal delivery in 1 (2%). In controls, full term normal vaginal delivery was in 41 (82%), PVD in 5 (10%), LSCS in 4 (8%). APGAR score <7 at 1 minute was in 19 (38%) and at 5 minutes was in 5 (10%) in cases. Birth weight is reduced in cases. IUGR was reported in 9 (18%) in cases.Conclusions: Pregnancies with Oligohydramnios (AFI≤5) is associated with increased rate of non-reactive NST. Routine induction of labor for Oligohydramnios is not recommended. It is preferable to allow patients to go into spontaneous labor with continuous FHR monitoring. Antepartum diagnosis of Oligohydramnios warrants close fetal surveillance

The persistence of equatorial spread F - an analysis on seasonal, solar activity and geomagnetic activity aspects

The persistence (duration) of Equatorial Spread F (ESF), which has significant impact on communication systems, is addressed. Its behavior during different seasons and geomagnetic activity levels under the solar maximum (2001) and minimum (2006) conditions, is reported using the data from the magnetic equatorial location of Trivandrum (8.5° N; 77° E; dip 0.5° N) in India. The study reveals that the persistence of the irregularities can be estimated to a reasonable extent by knowing the post sunset F region vertical drift velocity (Vz) and the magnetic activity index Kp. Any sort of advance information on the possible persistence of the ionospheric irregularities responsible for ESF is important for understanding the scintillation morphology, and the results which form the first step in this direction are presented and discussed