Optimum design of composite prestressed concrete girder railway bridges

This paper deals with the formulation of design optimisation of pretsressed concrete bridges. The bridge is of a slab-on-girder type, hence modeled as an equivalent orthotropic plate. The whole bridge system is considered as a simply supported right angle plate. Following linear elastic behaviour, the governing fourth order differential equation of the plate for patch load is solved in order to find out load distribution on the girders forming the bridge as well as the deflections and internal forces at critical sections of the whole bridge. The optimisation problem is formulated for various cross sectional geometries including rectangular, symmetrical I, unsymmetrical I, box, T and inverted T sections. The design variables are the main cross sectional dimensions, prestressing force and tendon eccentricity. The objective function comprises the cost of concrete material, formwork and prestressing steel tendons. The constraint functions are set to satisfy design requirements as per British Standards for bridges (BS 5400). Nonlinear optimisation method based on sequential unconstrained minimisation technique (SUMT) is employed to achieve optimum bridge configuration for specific design parameters of span length, concrete compressive strength and railway loading patterns. A purpose built computer program is set up to carry out the solution of the design optimisation problem efficiently in terms of time and effort. A typical example of unsymmetrical I-section having a small bottom flange as compared to the top flange width with composite deck effect is presented. The results show that the total cost increases as the span increases due to the increase of the initial prestressing force. Furthermore, the total cost decreases as the concrete compressive strength increases in spite of the increasing of the prestressing force. This is due to decrease of the overall depth, top and bottom flange widths, hence leading to a smaller girder size. Such finding will encourage engineers to adopt high strength concrete for bridges as it will help reducing not only the initial cost but also the life cycle cost of the bridge over its entire life

The impact of Organizational Citizenship Behavior on Job Performance at Greater Amman Municipality

This study aims to investigate the effect of organizational citizenship behavior, henceforth (OCB) on Job Performance in Amman Greater Municipality. One hundred and fifty responses have been collected  by means of questionnaire. Statistical analysis  techniques such as descriptive statistics and correlation, multiple regressions, are  employed. To confirm the suitability of data collection instrument, a Skewnes Coefficient test and Cronbach’s Alpha are used. The findings of this  study  supported the hypotheses that (OCB) positively impacts (JP) of Amman Greater Municipality. The  OCB factors have an  impact on job performance. This means that the perception of employees toward OCB has a positive and significant influence on employees performance. The  OCB factors have an impact on work volume ,on work quality ,employee-colleagues relationship as a dependent variable and on employee-higher level relationships. This study provides suitable recommendations on the scope for improvement based on current levels of various specific impact organizational citizenship behavior and its dimensions. Also the study provides suitable recommendations on the scope of improvement based on current levels of various predominant organizational citizenship behavior criteria that directly impact Job Performance of  Amman Greater Municipality. Key Words: Organizational citizenship behavior, Job Performance, Amman Greater Municipality

The Reliability and Validity of a MLCT-Scale for the Assessment of Kindergarten Children

This study was derived from the review of literature on motivation to learn, and creative thinking, in kindergarten children. While both these themes are explored reasonably in depth, there is very little research on motivation to learn creative thinking, which is a pillar of educational development. The researcher found the reason was that there was no Scale to measure this aspect, and so he constructed a new Motivation to Learn Creative Thinking Scale (MLCT-Scale) among kindergarten children. He also investigated the psychometric characteristics of the Scale. This Scale construction and investigation findings are reported here. The methodology used in this study was Descriptive survey. In all, 21 items formed the MLCT- scale within 5 dimensions. It uses a 5-points Likert Scale. Before conducting the Study, the two validities of the scale, concept and concurrent validities, were assessed. The study sample size was a random selection of 360 Kindergarten children, restricted to Amman city in Jordan. As this was a new Scale, the researcher took utmost care, through a series of statistical tests, to ensure Reliability, Concept validity and Construct validity of the Scale. He also ensured that the factor loading of each of the 21 items onto 5 factors was very strong. The study findings showed high coefficient correlations for Reliability, Concept and Concurrent Validity. There was a strong loading of the 5 scale dimensions as shown by Exploratory Factor Analysis. It is strongly recommended by the researcher that motivation to learn creative learning in kindergarten can be assessed by implementing the Motivating Children to Learn Creative Thinking Scale

A new splitting-based displacement prediction approach for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage

PRIIME: A generic framework for interactive personalized interesting pattern discovery

The traditional frequent pattern mining algorithms generate an exponentially large number of patterns of which a substantial proportion are not much significant for many data analysis endeavors. Discovery of a small number of personalized interesting patterns from the large output set according to a particular user's interest is an important as well as challenging task. Existing works on pattern summarization do not solve this problem from the personalization viewpoint. In this work, we propose an interactive pattern discovery framework named PRIIME which identifies a set of interesting patterns for a specific user without requiring any prior input on the interestingness measure of patterns from the user. The proposed framework is generic to support discovery of the interesting set, sequence and graph type patterns. We develop a softmax classification based iterative learning algorithm that uses a limited number of interactive feedback from the user to learn her interestingness profile, and use this profile for pattern recommendation. To handle sequence and graph type patterns PRIIME adopts a neural net (NN) based unsupervised feature construction approach. We also develop a strategy that combines exploration and exploitation to select patterns for feedback. We show experimental results on several real-life datasets to validate the performance of the proposed method. We also compare with the existing methods of interactive pattern discovery to show that our method is substantially superior in performance. To portray the applicability of the framework, we present a case study from the real-estate domain