Participation of Self Help Group Tribal Women in Economic and Social Developmental Activities

A study was taken up among the tribal women in the Nilgiris district mainly to assess the extent of participation of tribal women SHG members in various developmental activities.Kotagiri and Gudalur blocks were selected based on the presence of NGOs specifically working for the tribes. Totally eight SHGs have been randomly selected for the study. This comprises four each from Todas and Kattunayakas. A sample of 10 members from each SHGs have been randomly selected. Thus the total sample size is 80. The results indicated that the overall analysis indicate that majority (55.00%) of the tribal women hadmedium level of participation followed by high and low levels

A Pilot study to evaluate the feasibility, tolerance and efficacy of addition of hyperthermia to external beam radiotherapy (EBRT) on patients with locally advanced non metastatic inoperable head and neck cancer for palliation of symptoms

OBJECTIVES: To assess the feasibility and toxicity of hyperthermia with radiation in patients with locally advanced non metastatic head and neck cancers, to assess the palliation of distressing symptoms in them. METHODS: Ten patients diagnosed to have locally advanced head and neck cancers, were treated with radiotherapy to a dose of 66 Gy in 33 fractions in Cobalt 60 machine(conventional fractionation) along with once weekly sittings of hyperthermia. Hyperthermia was given 30 minutes before radiotherapy for 30 minutes. Descriptive statistics was done. Weekly toxicity was monitored by RTOG and CTCAE criteria. Pain and quality of life (EORTC questionnaire)) was assessed before and after treatment. Response was compared with CT scans 3 months after treatment with Wilcoxan sign test. Response was assessed by RECIST criteria. Survival analysis was done by Kaplan meier method. RESULTS: Among the 10 patients, 6 (60%) completed the treatment and 3(30%) without break. The incidence of grade 3 mucositis, grade 4 mucositis and grade 3 dermatitis was 42%, 14% and 28% respectively. The mean reduction in nodal size was 70% at 6 weeks. Pain control was good for a short duration (2 months), after which 50% of patients required STEP 3 analgesics. CONCLUSION: This treatment can be considered in patients with large, fixed nodes. Hyperthermia should be carried out with planned infrastructure and meticulous temperature monitoring and dosimetry

A study to evaluate the effectiveness of multisensory learning approach on academic performance of slow learners among school age children in a selected school at Kulasekharam

INTRODUCTION: Learning is considered to be a skill, both within and beyond the walls of the classroom. It depends upon the environmental stimulation, opportunities and guidance one is able to receive. Children with low learning skills are at a disadvantaged position when compared to children who can cope with the normal learning system. To ensure slow learners success in schools, their rate of slow learning to be accommodated through specifically designed interventions such as multisensory learning in accordance with their ability level. OBJECTIVE: The overall objective of the study was to assess the academic performance of slow learners, and to find out the effectiveness of multisensory approach on academic improvement of slow learners among school age children. METHODOLOGY: This study based on pre experimental one group pretest posttest design. Pilot study was conducted on 6 samples. After conducting the pilot study, A total of 60 samples were selected for the main study by purposive sampling technique. The investigator conducted a main study in a sample of 60 school age children with low learning ability. Verbal consent was obtained from the sample and confidentiality was maintained. Modified Zimmerman’s academic achievement rating scale was used to assess the academic performance of slow learners among school age children. It has 20 items related to academic and other areas of child’s performance. Data were analyzed by descriptive and inferential statistics. FINDINGS OF THE STUDY: The findings of the study revealed that the pretest mean score as 30.4 and the post test mean score as 60.1.A comparison was done between the pre and post test level of academic performance by paired “t” test. The t test value was 37.8 at p < 0.05, that was statistically highly significant. The association of demographic variables like age, gender, birth order, education and occupation of parents, type of family, living area of child and mode of study in home was tested by chi square test and was significant with level of academic performance. CONCLUSION: The study findings revealed that there is a significant improvement in the level of academic performance after using multisensory learning activities in their learning process. It has eventually helped to improve the academic performance of slow learners. Thus it may be considered as mandatory during their academic endeavor

Case study of Hyperparameter Optimization framework Optuna on a Multi-column Convolutional Neural Network

To observe the condition of the flower growth during the blooming period and estimate the harvest forecast of the Canola crops, the ‘Flower Counter’ application has been developed by the researchers ofP2IRC at the University of Saskatchewan. The model has been developed using a Deep Learning based Multi-column Convolutional Neural Network (MCNN) algorithm and the TensorFlow framework, in order to count the Canola flowers from the images based on the learning from a given set of training images. To ensure better accuracy score with respect to flower prediction, proper training of the model is essential involving appropriate values of hyperparameters. Among numerous possible values of these hyperparameters, selecting the suitable ones is certainly a time-consuming and tedious task for humans. Ongoing research for developing Automated Hyperparameter Optimization (HPO) frameworks has attracted researchers and practitioners to develop and utilize such frameworks to give directions towards finding better hyperparameters according to their applications. The primary goal of this research work is to apply the Automated HPO Optuna on the Flower Counterapplication with the purpose of directing the researchers towards among the best observed hyperparameter configurations for good overall performance in terms of prediction accuracy and resource utilization. This work would help the researchers and plant scientists gain knowledge about the practicality of Optuna while treating it as a black-box and apply it for this application as well as other similar applications. In order to achieve this goal, three essential hyperparameters, batch size, learning rate and number of epochs, have been chosen for assessing their individual and combined impacts. Since the training of the model depends on the datasets collected during diverse weather conditions, there could be factors that could impact Optuna’s functionality and performance. The analysis of the results of the current work and comparison of the accuracy scores with the previous work have yielded almost equal scores while testing the model’s performance on different test populations. Moreover, for the tuned version of the model, the current work has shown the potential for achieving that result with substantially lower resource utilization. The findings have provided useful concepts about making the better usage of Optuna; the search space can be restricted ormore complicated objective functions can be implemented to ensure better stability of the models obtained when chosen parameters are used in trainin

Optimization of Web-Based Hierarchical Workgroups to Automate Workflow

This project is aimed at developing web application which provide services for an education institution such as requesting leave, reserving books and posting suggestions. It is an Intranet based web-application which can be accessed by all the students and faculties throughout the department. A different access level login has been provided for students, faculties and the head of the department to access the services. This application can be used to automate the workflow of leave applications and their approvals. Through this application students can send a leave request to both the head of the department and the faculty. Each and every leave request of the students will be stored in the database. Thus the students who took leave frequently can be identified easily by the head of the department. There are options available for the students and faculties to reserve the books from the department library. A library catalogue has been provided with this application so that the desired books and magazines can be searched and reserved at anytime. After the reservation details are verified, the librarian or the managing staff will issue the books. In addition to this, department functions and upcoming events can be viewed through an event calendar. Innovative thoughts and ideas are always accepted by the department, the Feedback or Suggestion Box scheme provided by this application gives an opportunity for the students to give their creative idea and getting them to be implemented for achieving department excellenc

DHFormer: A Vision Transformer-Based Attention Module for Image Dehazing

Images acquired in hazy conditions have degradations induced in them. Dehazing such images is a vexed and ill-posed problem. Scores of prior-based and learning-based approaches have been proposed to mitigate the effect of haze and generate haze-free images. Many conventional methods are constrained by their lack of awareness regarding scene depth and their incapacity to capture long-range dependencies. In this paper, a method that uses residual learning and vision transformers in an attention module is proposed. It essentially comprises two networks: In the first one, the network takes the ratio of a hazy image and the approximated transmission matrix to estimate a residual map. The second network takes this residual image as input and passes it through convolution layers before superposing it on the generated feature maps. It is then passed through global context and depth-aware transformer encoders to obtain channel attention. The attention module then infers the spatial attention map before generating the final haze-free image. Experimental results, including several quantitative metrics, demonstrate the efficiency and scalability of the suggested methodology