Questions Asked to Valluvar by Harlots

This article signifies how one group of women, who should be the epitome of discipline, virtues, and mothers of nobles in society, have transformed into harlots for the sake of poverty and emotional hunger in the physical body by hurting themselves. The sublime subject of this article is to reflect on the way the government itself supports this and approves the same as how the fertile lands are converted into commercial lands. The drying tears of the harlots who happen to sell their physical bodies but spread the ray of dignity without selling their hearts are the nourishment for this society to become fertile. Considering the changes brought about in our society by the Tamil movements created during the contemporary period, the distinct part of this article captures the similarity between the expressions of the inner turmoil of the harlots in the new collection of poems 'Vanakkam Valluva' by the Tamil scholar 'Erode Tamilanpan' and the current scenario with illustrations from early and contemporary literary works

Veerayuga Nayagan Velpari is a Language and Life that Brings out new Ideas

Language is the life for human race and it is language that differentiates humans from other living things. Language is also a medium of exchange of information between human beings. Language has many meanings such as letter, word, syllable, term and so on. Words have spine-tingling power, and such words plays an important role in human life. This article explains how Venkatesan in his novel “Veerayuga Nayagan Velpari” has said about the elements of the language, writings and about the words and how they are interwined with the human life. Tolkappiyar's interpretation of some words, lifestyle of Parambu people, smoke language, daughter's language, business and language, language and love, language and the effects of language in the life of Parambu people have been highlighted in this article

Quantification of the abundance and diversity of predatory spiders in rice ecosystem of Rajendranagar, Telangana, India

The effective prey searching ability and polyphagy of spiders makes them important predators of crop pests. 19 species of spiders have been recorded in rice ecosystem (Rajeswaran et al., 2005). There is now a growing need to conserve all species and not only the large vertebrates (Samways, 1990) and contribute to the natural biological process. However, literature pertaining to their abundance and diversity in rice crop in Rajendranagar area is scant. Hence, the p resent study was conducted to understand their abundance and diversity. Spider samples were collected from rice fields of Rajendranagar in kharif and rabi seasons of 2011-12 and 2012-13. A total of 2,094 individuals collected in kharif represented eight families with a density of 12.48/sq.m. Members of Tetragnathidae were recorded most abundantly in kharif (46.32% of the Arachnid population) followed by Lycosids (26.22%). In rabi 1,095 spiders of seven families were collected with a density of 6.38/sq.m. Tetragnathidae andLycosidae were the most abundantly found species in rabi also comprising 27.85% and 26.12% of Arachnid population respectively. Study of guild composition was also carried out. A t-test between indices of richness, diversity, effective no.of species and species evenness of kharif and rabi seasons revealed that there were no significant differences with respect to these parameters (p>0.05) indicating that spider diversity of rice in Rajendranagar was more or less same between kharif and rabi seasons. This is the first study on the spider diversity of rice ecosystem of Rajendranagar, Hyderabad, India

Feasibility of bilateral salpingo-oophorectomy during vaginal hystertectomy for benign uterine diseases

Background: Prophylactic bilateral salpingo-oophorectomy (BSO) remains the best measure in the prevention of ovarian cancer as it lacks an effective screening tool. The need to perform prophylactic BSO shouldn't dictate the route of surgery. To assess the feasibility of prophylactic BSO during vaginal hysterectomy. To analyze the safety of the vaginal BSO.Methods: This was a retrospective study conducted in the Department of Obstetrics and Gynaecology at Velammal Medical College, Madurai, Tamilnadu, India from June 2016 to June 2018 over a period of 3 years. 54 women who underwent hysterectomy for benign uterine disease in whom concomitant prophylactic BSO was attempted were included in the study. Preoperative data like age, parity, menopausal status, BMI, previous pelvic surgeries were noted from the admission record. Intraoperative details like indication for surgery, surgical procedure, duration of surgery and complications like hemorrhage, bladder, ureter and bowel injury were collected from the operative record. Postoperative recovery details were also noted down from the case sheet. The collected data were then analyzed.Results: Of the 54 women included in the study, transvaginal BSO was successful in 53 (98.1%) women. There was one case of primary haemorrhage due to slippage of ovarian pedicle, another patient required laparotomy for completing BSO. None had bladder, ureter or bowel injury.Conclusions: Prophylactic BSO is both feasible and safe in almost all patients undergoing vaginal hysterectomy. Developing the skill to perform transvaginal BSO can inspire gynaecologists to move a step forward and deal with benign adnexal pathology concomitantly at vaginal hysterectomy. The risk of remnant ovarian syndrome post vaginal oophorectomy is unknown

Indoor Scene Recognition for Micro Aerial Vehicles Navigation using Enhanced-GIST Descriptors

An indoor scene recognition algorithm combining histogram of horizontal and vertical directional morphological gradient features and GIST features is proposed in this paper. New visual descriptor is called enhanced-GIST. Three different classifiers, k-nearest neighbour classifier, Naïve Bayes classifier and support vector machine, are employed for the classification of indoor scenes into corridor, staircase or room. The evaluation was performed on two indoor scene datasets. The scene recognition algorithm consists of training phase and a testing phase. In the training phase, GIST, CENTRIST, LBP, HODMG and enhanced-GIST feature vectors are extracted for all the training images in the datasets and classifiers are trained for these image feature vectors and image labels (corridor-1, staircase-2 and room-3). In the test phase, GIST, CENTRIST, LBP, HODMG and enhanced-GIST feature vectors are extracted for each unknown test image sample and classification is performed using a trained scene recognition model. The experimental results show that indoor scene recognition algorithm employing SVM with enhanced GIST descriptors produces very high recognition rates of 97.22 per cent and 99.33 per cent for dataset-1 and dataset-2, compared to kNN and Naïve Bayes classifiers. In addition to its accuracy and robustness, the algorithm is suitable for real-time operations

Construction of Permutation Polynomials of Certain Specific Cycle Structure over Finite Fields

For a finite field of odd number of elements we construct families of permutation binomials and permutation trinomials with one fixed-point (namely zero) and remaining elements being permuted as disjoint cycles of same length. Binomials and trinomials providing permutations with cycles of many lengths with certain frequency are also constructed.Comment: 10 pages, 1 table, Comments welcom

A Survey to Identify an Efficient Classification Algorithm for Heart Disease Prediction

Classification is one of the prominent data mining techniques. The objective of the classification algorithms is to place the data in the appropriate class. Data mining plays a vital role in medical diagnosis. The aim of this paper is to identify an efficient classification algorithm for cardiovascular disease prediction. The efficiency of each classification algorithm is expressed using two parameters namely accuracy and Root Mean Square Error (RMSE). From our experimental analysis, we infer that iterative classifier optimizer algorithm results in higher accuracy

Instrumental delivery: a comparative study in a tertiary care hospital

Background: To compare maternal and neonatal outcomes of vacuum versus forceps application in assisted vaginal delivery.Methods: Women in labor with vertex presentation were delivered by indicated/propylactic vacuum or forceps. A total of 500 cases were included in this retrospective study. Maternal and neonatal morbidity were compared in terms of perineal lacerations, episiotomy extension, post-partum hemorrhage, Apgar score, neonatal jaundice, perinatal mortality, NICU admissions etc. Chi square test was used to analyze the data.Results: Maternal morbidity was significant in the forceps group. With regards to neonatal morbidity, in NICU admissions, statistically significant difference was noted.Conclusions: Vacuum and forceps should remain appropriate tools in the modern obstetrics. However, ventouse may be chosen first (if there is no fetal distress) as it is significantly less likely to injure the mother and decrease NICU admissions

A Survey to Identify an Efficient Classification Algorithm for Heart Disease Prediction

Classification is one of the prominent data mining techniques. The objective of the classification algorithms is to place the data in the appropriate class. Data mining plays a vital role in medical diagnosis. The aim of this paper is to identify an efficient classification algorithm for cardiovascular disease prediction. The efficiency of each classification algorithm is expressed using two parameters namely accuracy and Root Mean Square Error (RMSE). From our experimental analysis, we infer that iterative classifier optimizer algorithm results in higher accuracy

Microelectromechnical Systems Inertial Measurement Unit Error Modelling and Error Analysis for Low-cost Strapdown Inertial Navigation System

This paper presents error modelling and error analysis of microelectromechnical systems (MEMS) inertial measurement unit (IMU) for a low-cost strapdown inertial navigation system (INS). The INS consists of IMU and navigation processor. The IMU provides acceleration and angular rate of the vehicle in all the three axes. In this paper, errors that affect the MEMS IMU, which is of low cost and less volume, are stochastically modelled and analysed using Allan variance. Wavelet decomposition has been introduced to remove the high frequency noise that affects the sensors to obtain the original values of angular rates and accelerations with less noise. This increases the accuracy of the strapdown INS. The results show the effect of errors in the output of sensors, easy interpretation of random errors by Allan variance, the increase in the accuracy when wavelet decomposition is used for denoising inertial sensor raw data.Defence Science Journal, 2009, 59(6), pp.650-658, DOI:http://dx.doi.org/10.14429/dsj.59.157