Pupils' Interaction with the Exhibits According to the Learning Behaviour Model

Science centres are one of the best opportunities for informal study of natural science. There are many advantages to learn in the science centres compared with the traditional methods: it is possible to motivate and supply visitors with the social experience, to improve people’s understandings and attitudes, thereby bringing on and attaching wider interest towards natural science. In the science centres, pupils show interest, enthusiasm, motivation, self-confidence, sensitiveness and also they are more open and eager to learn. Traditional school-classes however mostly do not favour these capabilities. This research presents the qualitative study in the science centre. Data was gathered from observations and interviews at Science North science centre in Canada. Pupils’ learning behaviours were studied at different exhibits in the science centre. Learning behaviours are classified as follows: labels reading, experimenting with the exhibits, observing others or exhibit, using guide, repeating the activity, positive emotional response, acknowledged relevance, seeking and sharing information. In this research, it became clear that in general pupils do not read labels; in most cases pupils do not use the guides help; pupils prefer exhibits that enable high level of interactivity; pupils display more learning behaviours at exhibits that enable a high level of interactivity.

Vad påverkar föräldrars sätt att tillgodose barns behov av regelbundet umgänge? : En applikation på Theory of Planned Behaviour

Föreliggande undersökning var en attitydundersökning baserad på Theory of Planned Behaviour där attityd, subjektiv norm, upplevd kontroll samt intention anses kunna predicera beteende. Syftet med undersökningen är försöka ta reda på vilka faktorer som påverkar hur mycket tid man som förälder umgås med sina barn efter en separation eller skilsmässa eftersom många barn i den situationen förlorar kontakten med den ena föräldern. 36 försöksdeltagare besvarade ett frågeformulär bestående av 31 frågor och påståenden gällande umgänge. Resultaten visar att tiden man som förälder umgås med sina barn efter en skilsmässa beror på intention och upplevd kontroll. Intentionen förklaras av upplevd kontroll och dom förväntningar man upplever från omgivningen. Attityden hade endast liten betydelse i modellen.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Behaviour of Surface Defects in Wire Rod Rolling

Defects are often present in rolled products, such as wire rod. The markets demand for wire rod without any defects has increased. In the final wire rod products, defects originating from the steel making, casting, pre-rolling of billets and during the wire rod rolling can appear. In this work, artificial V-shaped longitudinal surface cracks has been analysed experimentally and by means of FEM. The results indicate that the experiments and FEM calculations show the same tendency except in two cases, where instability due to a fairly “round” false round bars disturbed the experiment. FE studies in combination with practical experiments are necessary in order to understand the behaviour of the material flows in the groove and to explain whether the crack will open up as a V-shape or if it will be closed as an I-shape.

To what extent are CO2 emissions from intra-urban shopping trips by cars affected by drivers’ travel behaviour and store location?

Transportation is seen as one of the major sources of CO2 pollutants nowadays. The impact of increased transport in retailing should not be underestimated. Most previous studies have focused on transportation and underlying trips, in general, while very few studies have addressed the specific affects that, for instance, intra-city shopping trips generate. Furthermore, most of the existing methods used to estimate emission are based on macro-data designed to generate national or regional inventory projections. There is a lack of studies using micro-data based methods that are able to distinguish between driver behaviour and the locational effects induced by shopping trips, which is an important precondition for energy efficient urban planning. The aim of this study is to implement a micro-data method to estimate and compare CO2 emission induced by intra-urban car travelling to a retail destination of durable goods (DG), and non-durable goods (NDG). We estimate the emissions from aspects of travel behaviour and store location. The study is conducted by means of a case study in the city of Borlänge, where GPS tracking data on intra-urban car travel is collected from 250 households. We find that a behavioural change during a trip towards a CO2 optimal travelling by car has the potential to decrease emission to 36% (DG), and to 25% (NDG) of the emissions induced by car-travelling shopping trips today. There is also a potential of reducing CO2 emissions induced by intra-urban shopping trips due to poor location by 54%, and if the consumer selected the closest of 8 existing stores, the CO2 emissions would be reduced by 37% of the current emission induced by NDG shopping trips.