KAP Study on Immunization of Children in a City of North India – A 30 Cluster Survey

Background: To determine the knowledge, attitude and practices about immunization among respondents of children aged 12-23 months.\ud Methods: A total of 510 respondents were interviewed in the urban slums of Lucknow district of India, using 30 cluster sampling technique from January 2005 to April 2005. A pre-tested structured questionnaire was used to elicit the information about the knowledge, attitude and practices of the respondents regarding immunization. \ud Results: Knowledge regarding the disease prevented, number of doses and correct age of administration of BCG was highest among all the categories of respondents. The paramedical worker was the main source of information to the respondents of completely (52.0%) and partially immunized (48.5%) children while community leaders for unimmunized children. Those availing private facilities were more completely immunized, as compared to the government facilities. 55.8% of those who took 20 minutes to reach the immunization site were completely immunized as compared to 64.1% of those who took more than 20 minutes.\ud Conclusion: Considering the incomplete knowledge, and inappropriate practices of the people, the policy makers and medical professionals require Herculean efforts to raise the knowledge and to break the old beliefs of the peopl

A web-based software tool for participatory optimization of conservation practices in watersheds

WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) is a web-based, participatory planning tool that can be used to engage with watershed stakeholder communities, and involve them in using science-based, human-guided, interactive simulation–optimization methods for designing potential conservation practices on their landscape. The underlying optimization algorithms, process simulation models, and interfaces allow users to not only spatially optimize the locations and types of new conservation practices based on quantifiable goals estimated by the dynamic simulation models, but also to include their personal subjective and/or unquantifiable criteria in the location and design of these practices. In this paper, we describe the software, interfaces, and architecture of WRESTORE, provide scenarios for implementing the WRESTORE tool in a watershed community's planning process, and discuss considerations for future developments

User Modeling And Personalized Optimization For Stakeholder-Driven Watershed Design

We have developed a web-based, interactive, watershed planning system called WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) (http://wrestore.iupui.edu) that allows stake-holder communities to participate in a democratic, collaborative form of optimization process for designing best management practices (BMPs) on their landscape, while also optimizing based on subjective, qualitative landowners’ criteria beyond the usual socio-economic, physical, and ecological criteria. This system utilizes multiple advanced computational approaches including the SWAT (Soil and Water Assessment Tool) hydrologic model for watershed simulations, interactive genetic algorithms and reinforcement-based machine learning algorithms for search and optimization, and deep learning artificial neural networks for user modeling, within an encompassing human-computer interaction framework. A substantial user study of the WRESTORE system was conducted recently involving multiple real stakeholders varying from consultants, government officials, watershed alliance members, etc., with the objective of gaining insight about WRESTORE’s usability and utility. In particular focus was the user modeling component that develops a computational model of a user’s preferences and criteria, based on real-time user-provided ratings for a subset of possible designs (similar to the idea of user profiling commonly done for Information Filtering Systems). The user model constructed based on the real user’s personalized feedbacks can then be used to influence the automated search for and optimization of BMP alternatives in WRESTORE. In this paper, we describe the overall WRESTORE system architecture, the methods developed for user modeling for interactive optimization, and the experimental set-up as well as results with real user studies. These results clearly demonstrate that development of user models for such personalized, interactive optimization is both feasible and valuable for developing community-based computational water sustainability solutions

User modeling and optimization for environmental planning system design

Environmental planning is very cumbersome work for environmentalists, government agencies like USDA and NRCS, and farmers. There are a number of conflicts and issues involved in such a decision making process. This research is based on the work to provide a common platform for environmental planning called WRESTORE (Watershed Restoration using Spatio-Temporal Optimization of Resources). We have designed a system that can be used to provide the best management practices for environmental planning. A distributed system was designed to combine high performance computing power of clusters/supercomputers in running various environmental model simulations. The system is designed to be a multi-user system just like a multi-user operating system. A number of stakeholders can log-on and run environmental model simulations simultaneously, seamlessly collaborate, and make collective judgments by visualizing their landscapes. In the research, we identified challenges in running such a system and proposed various solutions. One challenge was the lack of fast optimization algorithm. In our research, several algorithms are utilized such as Genetic Algorithm (GA) and Learning Automaton (LA). However, the criticism is that LA has a slow rate of convergence and that both LA and GA have the problem of getting stuck in local optima. We tried to solve the multi-objective problems using LA in batch mode to make the learning faster and accurate. The problems where the evaluation of the fitness functions for optimization is a bottleneck, like running environmental model simulation, evaluation of a number of such models in parallel can give considerable speed-up. In the multi-objective LA, different weight pair solutions were evaluated independently. We created their parallel versions to make them practically faster in computation. Additionally, we extended the parallelism concept with the batch mode learning. Another challenge we faced was in User Modeling. There are a number of User Modeling techniques available. Selection of the best user modeling technique is a hard problem. In this research, we modeled user\u27s preferences and search criteria using an ANN (Artificial Neural Network). Training an ANN with limited data is not always feasible. There are many situations where a simple modeling technique works better if the learning data set is small. We formulated ways to fine tune the ANN in case of limited data and also introduced the concept of Deep Learning in User Modeling for environmental planning system

Drying Characteristics of Plum Tomato under Different Physical Treatments for Producing Powder

Plum tomatoes were dried under hot air convection for producing powder. Different physical treatments were performed to achieve faster drying and milling. Initial moisture of tomato was 93.97 % with TSS of 4.6 %, which was dried to around 5 % moisture. Among the treatments, longitudinally cut in 16 pieces and cross-section slice segments took less time to dry and gave higher (6.4 %) drying yield. The effectiveness of treatments on drying characteristics and quality of tomato powder were examined. Mathematical models were employed by non-linear regression analysis to appropriately describe the drying behaviours. The physico-chemical quality characteristics of fresh and powder tomato were evaluated in terms of size and shape, peel pulp seed ratio, TSS, ascorbic acid, acidity, lycopene and solubility. The overall sensory perception revealed that all treatment samples of tomato powder reconstituted well in the form of soup-mix and achieved nearly equal scores on different quality attributes

A web-based software tool for participatory optimization of conservation practices in watersheds

WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) is a web-based, participatory planning tool that can be used to engage with watershed stakeholder communities, and involve them in using science-based, human-guided, interactive simulation–optimization methods for designing potential conservation practices on their landscape. The underlying optimization algorithms, process simulation models, and interfaces allow users to not only spatially optimize the locations and types of new conservation practices based on quantifiable goals estimated by the dynamic simulation models, but also to include their personal subjective and/or unquantifiable criteria in the location and design of these practices. In this paper, we describe the software, interfaces, and architecture of WRESTORE, provide scenarios for implementing the WRESTORE tool in a watershed community's planning process, and discuss considerations for future developments

A study on determinants of immunization coverage among 12-23 months old children in urban slums of Lucknow district, India

Context: To find out the suitable factors for raising the coverage of immunization. Aims : To determine the coverage and to identify the various factors of primary immunization. Settings and Design : Urban slums of Lucknow district. Methods and Material : WHO 30-cluster sampling technique was used for the selection of the subjects. Mother, father or relative of a total of 510 children with 17 children per cluster were interviewed in the study. Statistical Analysis : Chi-square test, binary logistic regression and multinomial logistic regression analysis were done to test the statistical significance of the association. Results: About 44% of the children studied were fully immunized. Multinomial logistic regression analysis revealed that an illiterate mother (OR=4.0), Muslim religion (OR=2.5), scheduled caste or tribes (OR=2.3) and higher birth order (OR≈2) were significant independent predictors of the partial immunized status of the child; while those associated with the unimmunized status of the child were low socioeconomic status (OR=10.8), Muslim religion (OR=4.3), higher birth order (OR=4.3), home delivery (OR=3.6) and belonging to a joint family (OR=2.1). Conclusions: The status of complete immunization is about half of what was proposed to be achieved under the Universal Immunization Program. This emphasizes the imperative need for urgent intervention to address the issues of both dropout and lack of access, which are mainly responsible for partial immunization and nonimmunization respectively

A web-based software tool for participatory optimization of conservation practices in watersheds

WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) is a web-based, participatory planning tool that can be used to engage with watershed stakeholder communities, and involve them in using science-based, human-guided, interactive simulation–optimization methods for designing potential conservation practices on their landscape. The underlying optimization algorithms, process simulation models, and interfaces allow users to not only spatially optimize the locations and types of new conservation practices based on quantifiable goals estimated by the dynamic simulation models, but also to include their personal subjective and/or unquantifiable criteria in the location and design of these practices. In this paper, we describe the software, interfaces, and architecture of WRESTORE, provide scenarios for implementing the WRESTORE tool in a watershed community's planning process, and discuss considerations for future developments.Keywords: Web-based, Participatory design, Watershed planning and management, Interactive optimization, Conservation practices, Subjective criteri