Learning Experience of Small Farmers in Sugarcane Cultivation

The effective learning experience can be had effective learning situations provided by a skillful instructor who knows what he wants, who has the materials to accomplish his goals and the skills to use them effectively. The study was conducted in Cuddalore district of Tamil Nadu. A total number of ten sugarcane technologies with technical units were selected for the study. The result of the study small farmers possessed low level of learning experience. The learning experience may be further enhanced by majority of the small farmers to prefer personal localite channels for getting information

Active Vibration Control of Piezolaminated Smart Beams

This paper deals with the active vibration control of beam like structures with distributed piezoelectric sensor and actuator layers bonded on top and bottom surfaces of the beam. A finite element model based on Euler-Bernoulli beam theory has been developed. The contribution of the piezoelectric sensor and actuator layers on the mass and stiffness of the beam is considered. Three types of classical control strategies, namely direct proportional feedback, constant-gain negative velocity feedback and Lyapunov feedback and an optimal control strategy, linear quadratic regulator (LQR) scheme are applied to study their control effectiveness. Also, the control performance with different types of loading, such as impulse loading, step loading, harmonic and random loading is studie

Breast Cancer Classification by Gene Expression Analysis using Hybrid Feature Selection and Hyper-heuristic Adaptive Universum Support Vector Machine

Comprehensive assessments of the molecular characteristics of breast cancer from gene expression patterns can aid in the early identification and treatment of tumor patients. The enormous scale of gene expression data obtained through microarray sequencing increases the difficulty of training the classifier due to large-scale features. Selecting pivotal gene features can minimize high dimensionality and the classifier complexity with improved breast cancer detection accuracy. However, traditional filter and wrapper-based selection methods have scalability and adaptability issues in handling complex gene features. This paper presents a hybrid feature selection method of Mutual Information Maximization - Improved Moth Flame Optimization (MIM-IMFO) for gene selection along with an advanced Hyper-heuristic Adaptive Universum Support classification model Vector Machine (HH-AUSVM) to improve cancer detection rates. The hybrid gene selection method is developed by performing filter-based selection using MIM in the first stage followed by the wrapper method in the second stage, to obtain the pivotal features and remove the inappropriate ones. This method improves standard MFO by a hybrid exploration/exploitation phase to accomplish a better trade-off between exploration and exploitation phases. The classifier HH-AUSVM is formulated by integrating the Adaptive Universum learning approach to the hyper- heuristics-based parameter optimized SVM to tackle the class samples imbalance problem. Evaluated on breast cancer gene expression datasets from Mendeley Data Repository, this proposed MIM-IMFO gene selection-based HH-AUSVM classification approach provided better breast cancer detection with high accuracies of 95.67%, 96.52%, 97.97% and 95.5% and less processing time of 4.28, 3.17, 9.45 and 6.31 seconds, respectively

A Deep CNN Framework for UAV Intrusion Detection in Intelligent Systems

Unmanned Ariel Vehicle (UAV) s are dealing with several safety and protection issues including internal hardware/software and potential attacks. In addition, detecting UAV anomalies will be a crucial responsibility to defend against hostile enemies and prevent accidents. In this research, we present a UAV and an Automatic Dependent (AD) system using surveillance and Machine Learning (ML) algorithms to analyze data from their detectors in real-time. Proposed Improved Region based Convolutional Neural Network (IRCNN) model used to generate and acquire the characteristics of untreated sensor information and characteristics to facilitate AD. The proposed model creating an Inertial Measurement Unit (IMU) & UAV sensors dataset using cyber security simulation system and Active Learning (AL) identifies aggressions based on the least probable interrogation method. This proposed model enables the identification to efficiently improve the occurrences of unexplained aggressions discovered of IRCNN at reduced labeling cost. A thorough trial showed that IRCNN-AL is effective at detecting unknown threats with frequency improvements of between 9% and 30% on comparison approaches. The AL methodology presented with as few as 1% of a labeled unexpected aggressions

Financial Investment Pattern and Preference of College Professors at Trichy City

Financial Investments are the commitments that are made by individuals with any financial and non-financial instruments for gaining a better and profitable return in future for a particular objective. The financial and non-financial investment instruments act as a medium or a driving tool for investment decisions of individuals. From the available investment avenues one must select the appropriate one that he feels safer or good to invest. The person who is going to make investments should be aware of all knowledge about investments and should be aware of how it is going to fulfil his objective. The person who is investing should be known of all the investment avenues available for making investments. Such avenues are employee provident fund, public provident fund, mutual funds, insurance, bank deposits, real estate, gold, stock market. This study is about to analyse the investment pattern of college professors and their attitude towards investment avenues. It also aims to identify the reason behind making investment and to find their objective for making investment. It helps to find the behaviour of individuals while making investments. Further this study helps to find the relationship of various demographic factors of the respondents and factors associated while making investment decisions. Such factors include time period of their investment, investment avenues, risk factors, returns etc

EFFECT OF CIRCADIAN OSCILLATION DURING FOOD DEPRIVATION ON HEART RATE IN OBESE MEN

The purpose of the study was to find out the effect of circadian oscillation during food deprivation on heart rate among obese men. To achieve the purpose of the present study, sixty obese men from Islamiah College, Vaniyambadi, Tamilnadu, India were selected as subjects at random and their ages ranged from 18 to 25 years. The subjects were divided into four equal groups of fifteen subjects each. Group I acted as Experimental Group I (Food Deprivation Training), Group II acted as Experimental Group II (Physical training), Group III acted as Experimental Group III (Food Deprivation & Physical training) and Group IV acted as Control Group. The requirement of the experiment procedures, testing as well as training schedule was explained to the subjects so as to get full co-operation of the effort required on their part and prior to the administration of the study. Heart rate was assessed by using stethoscope. Experimental Group I was exposed to food deprivation training, Experimental Group II was exposed to physical training, Experimental Group III was exposed to food deprivation & physical training and Control Group was not exposed to any experimental training other than their regular daily activities. The duration of experimental period was 120 days. After the experimental treatment, all the sixty subjects were tested on heart rate. This final test scores formed as post test scores of the subjects. The pre test and post test scores were subjected to statistical analysis using Analysis of Covariance (ANCOVA) to find out the significance among the mean differences, whenever the ‘F’ ratio for adjusted test was found to be significant, Scheffe’s post hoc test was used. In all cases 0.05 level of significance was fixed to test hypotheses. The findings of the study showed that the combined food deprivation and physical training group showed changes in heart rate than the other experimental and control groups

Shape Optimisation of Curved Interconnecting Ducts

Practical ducting layout in process plants needs to satisfy a number of on-site constraints. The search for an optimal flow path around the obstructions is a multi-parameter problem and is computationally prohibitively expensive. In this study, authors proposed a rapid and efficient methodology for the optimal linkage of arbitrarily oriented fluid flow ducts using a single-parameter quadratic/cubic Bézier curves in two/three dimensions to describe the centreline of the curved duct. A smooth interconnecting duct can then be generated by extruding the duct face along the curve. By varying the parameter either along the angular bisector or along the axes of the ducts, a family of Bézier curves is generated. Computational fluid dynamics simulations show that the relationship between pressure drop and the adjustable parameter is a unimodal curve and the optimal connecting duct is the one which has the least pressure drop while satisfying on-site constraints can be used for linking the ducts. The efficacy of the method is demonstrated by applying it to some cases of practical interest.Defence Science Journal, Vol. 65, No. 4, July 2015, pp. 300-306, DOI: http://dx.doi.org/10.14429/dsj.65.8353

Postbuckling Behaviour of Anisotropic Laminated Composite Plates due to Shear Loading

This study investigates postbuckling behaviour of laminated composite plates using a nine-noded shear flexible quadrilateral plate element. The formulation includes nonlinear strain-displacement relation based on von Karman's assumption. The nonlinear governing equations are solved through iteration. A detailed parametric study is carried out to bring out the influence of ply-angle, aspect ratio and material properties on the postbuckling strength of laminates due to in-plane shear loads

A study on antimicrobial sensitivity pattern in Neisseria gonorrhoeae in a tertiary care hospital

Background: Sexually transmitted diseases are prevalent throughout the world. Sexually transmitted diseases (STD) play a major role in the transmission of HIV infection. The risk of acquiring HIV infection in non-ulcerative STD is 3 to 5 times more than that in persons without any sexually transmitted infections. One of the main non-ulcerative STD is gonorrhoea. The relative incidence of gonococcal infections is about 10 to 13% of total sexually transmitted infections in STD clinics. Aims and objectives was to identify gonococcal infection in patients attending the STD clinic and associated sexually transmitted infections and to study the antimicrobial susceptibility of gonococcus and to modify the disease intervention strategies.Methods: A retrospective study was conducted in our institute of venereology, government general hospital and madras medical college, Chennai-03, Tamil Nadu, India. 43 patients with gram stained smear or culture positive for gonococcus who attended the institute from February 2013 to September 2014 were taken into the study. All the details were collected from the case records of the patients. The antibiotic sensitivity testing in N. gonorrhoeae had been done by Kirby-Bauer disc diffusion method. Screening for other sexually transmitted diseases had been done and were treated according to the institute guidelines.Results: Specimens from 43 patients (40 male, 3 females) had been collected. 40 specimens were found to be culture positive. Antibiotic sensitivity tests were carried out on those 40 isolates of Neisseria gonorrhoeae obtained in pure culture. 70% of isolates were resistant to penicillin and 30% were less sensitive to it. 52.5% of the isolates were PPNG. 57.5% of isolates were resistant to ciprofloxacin and 42.5% were less sensitive to it. 7.5% were resistant to ceftriaxone, 12.5% were resistant to cefixime and 15% were resistant to spectinomycin. All the isolates were sensitive to Azithromycin. Three male patients had HIV (6.9%), three had syphilis and one had genital wart. One female patient had trichomoniasis.Conclusions: The results of the study indicate that multidrug resistant Neisseria gonorrhoeae is prevalent in this region. Associated STDs must be investigated to prevent the transmission of HIV and further complications. The need for establishing a national surveillance programme for antibiotic resistance becomes clear with this study