Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

The economics of chemical industry in kerala

The main purpose of the present study is to examine the growth and development problems of a new industry ,the chemical industry in the state of kerala. Problems of productivity and efficiency are studied with respect to the different branches of the industry such as fertilizers and insecticides basic inorganic and organic chemicals drugs and pharmaceuticals and miscellaneous chemicals. A study of partial input output linkages between the different chemical units is also attempted. The chemical industry is generally characterized by high linkage effects .These linkages could be used to generate subsidiary industries and thereby help in the growth and diversification of the industry. The efficiency of the working of individual units is also studied to understand the problems involved and to suggest remedial measures.

Rapid and Proactive Approach on Exploration of Database Vulnerabilities

In today's complicated computing environment, managing data has become the primary concern of all industries. Information security is the greatest challenge and it has become essential to secure the enterprise system resources like the databases and the operating systems from the attacks of the unknown outsiders. Our approach plays a major role in detecting and managing vulnerabilities in complex computing systems. It allows enterprises to assess two primary tiers through a single interface as a vulnerability scanner tool which provides a secure system which is also compatible with the security compliance of the industry. It provides an overall view of the vulnerabilities in the database, by automatically scanning them with minimum overhead. It gives a detailed view of the risks involved and their corresponding ratings. Based on these priorities, an appropriate mitigation process can be implemented to ensure a secured system. The results show that our approach could effectively optimize the time and cost involved when compared to the existing systems

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.

Learning-Based Approach to Estimation of Morphable Model Parameters

We describe the key role played by partial evaluation in the Supercomputing Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial evaluation. The Supercomputing Toolkit parallel processor and its associated partial evaluation-based compiler have been used extensively by scientists at MIT, and have made possible recent results in astrophysics showing that the motion of the planets in our solar system is chaotically unstable.

Numerical comparison between Maxwell stress method and equivalent multipole approach for calculation of the dielectrophoretic force in octupolar cell traps

This work presents detailed numerical calculations of the dielectrophoretic force in octupolar traps designed for single-cell trapping. A trap with eight planar electrodes is studied for spherical and ellipsoidal particles using an indirect implementation of the boundary element method (BEM). Multipolar approximations of orders one to three are compared with the full Maxwell stress tensor (MST) calculation of the electrical force on spherical particles. Ellipsoidal particles are also studied, but in their case only the dipolar approximation is available for comparison with the MST solution. The results show that the full MST calculation is only required in the study of non-spherical particles.

Research Methods courses run in the University of Southampton

A listing from Banner of all courses (listed by School and level) run in the university that relate to research and inquiry. There is a crude attempt to cluster these courses thematically.

Research plan discussion: The socio-technical construction of MOOCs and educator practices in HE

In this seminar slot, we will discuss Steve's research aims and plan. Massive open online courses (MOOCs) have received substantial coverage in mainstream sources, academic media, and scholarly journals, both negative and positive. Numerous articles have addressed their potential impact on Higher Education systems in general, and some have highlighted problems with the instructional quality of MOOCs, and the lack of attention to research from online learning and distance education literature in MOOC design. However, few studies have looked at the relationship between social change and the construction of MOOCs within higher education, particularly in terms of educator and learning designer practices. This study aims to use the analytical strategy of Socio-Technical Interaction Networks (STIN) to explore the extent to which MOOCs are socially shaped and their relationship to educator and learning designer practices. The study involves a multi-site case study of 3 UK MOOC-producing universities and aims to capture an empirically based, nuanced understanding of the extent to which MOOCs are socially constructed in particular contexts, and the social implications of MOOCs, especially among educators and learning designers.

Impact on the quality of learning as a result of the use of computers in schools

The educational software and computer assisted learning has been used in schools to promote the interest of students in new ways of thinking and learning so it can be useful in the reading learning process. Experimental studies performed in preschool and school age population have shown a better yield and a positive effect in reading, mathematics and cognitive skills in children who use educative software for fi fteen to twenty minutes a day periods. The goal of this study was to evaluate the progression in verbal, visual-motor integration and reading skills in children who were using educational software to compare them with a group in traditional pedagogic methodology. Results: All children were evaluated before using any kind of pedagogic approach. Initial evaluation revealed a lower–age score in all applied test. 11% of them were at high risk for learning disorders. There was a second evaluation that showed a significant positive change compared with the fi rst one. Nevertheless, despite some items, there were no general differences comparing the groups according if they were using or not a computer. In conclusion, policies on using educational software and computers must be revaluated due to the fact that children in our public schools come from a deprived environment with a lack of opportunities to use technologies.

Clinical experience of clobazam as add-on treatment in a cohort of adults with epilepsy

Objective: Epilepsy is a common neurologic disorder affecting 1% of the world population with one-third of these patients failing to have seizure control for more than one year. Clobazam is a long-acting benzodiazepine used worldwide for the treatment of epilepsy. This antiepileptic drug has demonstrated great clinical benefits with mild side effects. The objective of this study was to better understand the efficacy of clobazam treatment on adult patients with refractory epilepsy. Design: A retrospective review of 44 adult patients with diagnosis of epilepsy that were seen at our Epilepsy Clinic between January 2014 and May 2015. Setting: An outpatient epilepsy clinic at the Hospital Universitario Fundación Santa Fe de Bogota, Colombia. Participants: 44 adult patients with diagnosis of epilepsy. Measurements: Seizure frequency, adverse effects and the use of concomitant AEDs were reviewed in each of the patient´s clinical charts. Results: The responder rate of patients with clobazam was 52% at 3 months, 50% at 6 months and 55% at 12 month. Seizure freedom rates at 3, 6 and 12 months were 18%, 25% and 25% respectively. Clobazam related adverse events occurred only in four patients (9%) at the end of the twelve months with somnolence being the most common. Conclusion: These findings suggest that clobazam treatment in adult patients with focal or generalized epilepsy is effective and safe. Its use should be considered early when first-line agents fail to provide seizure control.

El rendimiento diferido del proceso didáctico (Análisis input-output en función del autodiagnóstio del éxito de la vida).

Trata de conocer hasta qué punto la valoración académica de un individuo incide en la vida posterior del mismo, es decir, cuál puede ser el rendimiento de una persona en función del proceso educativo que haya seguido. Alumnos de cuarto de Bachiller, de edad comprendida entre 13 y 14 años que realizaron sus estudios en Cheste durante los cursos académicos de 1970-1971 y 1971-1972, con el Plan vigente de 1967. En total son 681 alumnos de los cuales el 53,86 por ciento pertenecen a zonas rurales y el 46,14 por ciento a zona urbana. En primer lugar trata teoriza sobre los estudios realizados de caracter input-output, tanto en el campo de la psicología como de la educación siendo consciente de esta forma de los problemas que los mismos dan y a los que deberá enfrentarse, posteriormente plantea el estudio realizando la investigación, seleccionando las variables que pretende estudiar, recogiendo datos , codificándolos, escogiendo una muestra de población y aplicando dichas variables para poder llegar a las conclusiones que finalmente ofrece el estudio y abriendo puertas a otros de las mismas carcterísticas. Encuesta, cuestionario, entrevista personal, test (AMPE). Variables input, dentro de las cuales se encuentran las variables estado (datos psicológicos), y las variables de flujo (rendimiento académico). Como variables psicológicas se consideran la actitud para el estudio, personalidad paranoide versus control, capacidad intelectual, extraversión. Como variables de rendimiento se estudia el rendimiento en cuarto de bachiller, el rendimiento en tercero de bachiller y destrezas físico-deportivas. Como variables de salida output se considera la situación laboral ocupacional, situación personal, situación económica y situación social. Análisis factorial, regresión múltiple, correlación de Pearson, análisis imput-output. Los resultados se encuentran implícitos en las siguientes conclusiones: 1) Los componenenes académicos influyen poco en la vida posterior del sujeto, si bien marcan o detectan en algún sentido su situación social convivencial sobre los demás aspectos. Ello nos induce a pensar que en el aula se califican a la vez que conocimientos, los comportamientos sociales. 2)Los componentes psicológicos influyen más en la situación personal entre los outpurs considerados 3)En el análisis input-output hay que destacar que los outputs no se explican en su totalidad con los inputs que hemos estudiado, lo que destaca la introduccion de muchas otras variables en la consideración de los aspectos tratados y éstas en gran cantidad.

Methodology in language teaching : an anthology of current practice.

Ofrece una visión general de los enfoques actuales, problemas y prácticas en la enseñanza del inglés como segundo idioma. La antología contiene más de cuarenta artículos ,organizados en dieciséis secciones, publicados principalmente en la última década. Presenta un panorama general de la enseñanza del inglés e ilustra la complejidad de la planificación de muchas actividades fundamentales. Estas actividades incluyen la enseñanza del inglés en primaria, secundaria y enseñanza superior; formación del profesorado. Examina los conocimientos lingüísticos; planes de estudio y desarrollo de materiales, el uso de computadoras y otras tecnologías en la enseñanza, así como la investigación sobre diferentes aspectos del aprendizaje de un segundo idioma. También se incluyen dos series de preguntas de discusión: un conjunto de antecedentes prelectura y una reflexión posterior a la lectura.

The experience of security in mathematics

Resumen basado en el de la publicaci??n