Tunable diode Laser Absorption Spectroscopy ,Nir Overtone and Life Studies of Some Organic Compound

The present work is mainly concentrated on setting up a NIR tunable diode laser absorption (TDLA) spectrometer for high-resolution molecular spectroscopic studies. For successfully recording the high-resolution tunable diode laser spectrum, various experimental considerations are to be taken into account like the setup should be free from mechanical vibrations, sample should be kept at a low pressure, laser should be in a single mode operation etc. The present experimental set up considers all these factors. It is to be mentioned here that the setting up of a high resolution NIR TDLA spectrometer is a novel experiment requiring much effort and patience. The analysis of near infrared (NIR) vibrational overtone spectra of some substituted benzene compounds using local mode model forms another part of the present work. An attempt is made to record the pulsed laser induced fluorescence/Raman spectra of some organic compounds. A Q-switched Nd:YAG laser is used as the excitation source. A TRIAX monochromator and CCD detector is used for the spectral recording. The observed fluorescence emission for carbon disulphide is centered at 680 nm; this is assigned as due to the n, p* transition. Aniline also shows a broad fluorescence emission centered at 725 nm, which is due to the p,p* transition. The pulsed laser Raman spectra of some organic compounds are also recorded using the same experimental setup. The calibration of the set up is done using the laser Raman spectra of carbon tetrachloride and carbon disulphide. The observed laser Raman spectra for aniline, o-chloroaniline and m-chlorotoluene show peaks characteristics of the aromatic ring in common and the characteristics peaks due to the substitutuent groups. Some new peaks corresponding to low-lying vibrations of these molecules are also assigned

Development of Zero Water Exchange Shrimp Culture System Integrated With Bioremediation of Detritus and Ammonia- Nitrogen

Aquaculture is one of the fastest growing food sectors in the world. Amongst the various branches of aquaculture, shrimp culture has expanded rapidly across the globe because of its faster growth rate, short culture period, high export value and demand in the International market. Indian shrimp farming has experienced phenomenal development over the decades due to its excellent commercial viability. Farmers have adopted a number of innovative technologies to improve the production and to maximize the returns per unit area. The culture methods adopted can be classified in to extensive, modified extensive and semi intensive based on the management strategies adopted in terms of pond size, stocking density, feeding and environmental control. In all these systems water exchanges through the natural tidal effects, or pump fed either from creek or from estuaries is a common practice. In all the cases, the systems are prone to epizootics due to the pathogen introduction through the incoming water, either brought by vectors, reservoir hosts, infected tissue debris and free pathogens themselves. In this scenario, measures to prevent the introduction of pathogen have become a necessity to protect the crop from the onslaught of diseases as well as to prevent the discharge of waste water in to the culture environment.The present thesis deals with Standardization of bioremediation technology for zero water exchange shrimp culture system

Significance Of Classification Techniques In Prediction Of Learning Disabilities

The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and clustering are powerful and popular tools used for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. Clustering is the assignment of a set of observations into subsets, called clusters, which are useful in finding the different signs and symptoms (attributes) present in the LD affected child. In this paper, J48 algorithm is used for constructing the decision tree and K-means algorithm is used for creating the clusters. By applying these classification techniques, LD in any child can be identified

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

A System for Offline Recognition of Handwritten Characters in Malayalam Script

In this paper, we propose a handwritten character recognition system for Malayalam language. The feature extraction phase consists of gradient and curvature calculation and dimensionality reduction using Principal Component Analysis. Directional information from the arc tangent of gradient is used as gradient feature. Strength of gradient in curvature direction is used as the curvature feature. The proposed system uses a combination of gradient and curvature feature in reduced dimension as the feature vector. For classification, discriminative power of Support Vector Machine (SVM) is evaluated. The results reveal that SVM with Radial Basis Function (RBF) kernel yield the best performance with 96.28% and 97.96% of accuracy in two different datasets. This is the highest accuracy ever reported on these datasets

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

An Encoded Infrared Sheet Of Light Navigational Beacon System For Precise Localization Of Indoor Mobile Robot Vehicles

A new localization approach to increase the navigational capabilities and object manipulation of autonomous mobile robots, based on an encoded infrared sheet of light beacon system, which provides position errors smaller than 0.02m is presented in this paper. To achieve this minimal position error, a resolution enhancement technique has been developed by utilising an inbuilt odometric/optical flow sensor information. This system respects strong low cost constraints by using an innovative assembly for the digitally encoded infrared transmitter. For better guidance of mobile robot vehicles, an online traffic signalling capability is also incorporated. Other added features are its less computational complexity and online localization capability all these without any estimation uncertainty. The constructional details, experimental results and computational methodologies of the system are also described

Does the actual transportation system covers the need of an integrated transportation system in Bogota

El problema de transporte en Bogotá es cada vez algo mas grande, pues las medidas actuales y los planes a futuro para el desarrollo de un sistema integrado de transporte parecen no ser suficientes para la magnitud poblacional de la capital Colombiana; de igual manera los precios son elevados y representan un inconveniente para los ciudadanos puesto que la cantidad de estos que puede pagar un pasaje del actual sistema transmilenio es cada vez más baja debido al alto incremento que su tarifa tiene anualmente. Por esta razón durante lo largo de este escrito se justificaran las razones que indican que los planes aplicados y por aplicar por el distrito no son suficientes para cubrir el vacío que existe en Bogotá a nivel de un sistema integrado de transporte público.

Identification of the Learning Styles in the Students of Exercise Physiology in the Rehabilitation and Human Development Faculty

The object of this study is to identify the learning styles (LS) used by the students of the subject of physiology of the exercise of the program of Physiotherapy, with the purpose of establishing a direct relationship later on between the learning styles and the possible pedagogic strategies that but they favor the compression of the physiology of the exercise 48 subject of second and third year of career they were interviewed through the instrument standardized compound number (CHAEA). This study carried out an analysis descriptive and of typical deviation of the data. They were differences statistically significant in the styles of active and reflexive learning, in front of the Theoretical and pragmatic styles what puts in evidence the necessity to generate pedagogic strategies inside the subject that this chord with the tendency of the active and reflexive learning of the students.

Learning through enquiry : making sense of geography in the key stage 3 classroom.

Está destinado al apoyo de los profesores en su desarrollo profesional, pues es una referencia útil para aquellos que quieran conocer temas de investigación en pedagogía geográfica. Aunque los ejemplos se han tomado principalmente de las escuelas de Inglaterra, pueden ser aplicados a las aulas de geografía de todo el mundo. También muestra cómo es el aprendizaje de la geografía promovido por la autora del libro, que favorece la participación activa de los estudiantes, al demostrar la importancia de estimular su curiosidad y promover un comportamiento crítico hacia los datos, y ofrecer, asimismo, oportunidades para qué los propios alumnos busquen nuevas ideas e información y reflexionen sobre lo aprendido.

Interpretation, emotional reactions and daily life implications of hallucination-like experiences in clinical and nonclinical populations

Resumen tomado de la publicaci??n

Providing pervasive learning eXperiences by combining Internet of Things and e-Learning standard

Resumen basado en el de la publicaci??n

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process