The comprehensive reasons for the cross-regional flow of enterprises in their own economy are studied this paper. Most traditional enterprise migration research focuses on impact a single factor. Even influence multiple factors often ignores interaction various factors. Therefore, paper proposes and logicalises “push pull” mechanism to address limitations previous research. Through bibliometric...

With the growing numbers of status update websites and related wrappers, initiatives modelling sensor data in RDF, as well as the dynamic nature of many Linked Data exporters, there is a need for protocols enabling real-time notification and broadcasting of RDF data updates. In this paper we present a flexible approach that provides such notifications to be delivered in real-time to any RSS or ...

the aim of this study was to investigate the effect of external intervention factor (types of music) on physical fitness factors in adolescent boys. 30 adolescent boys (9-12 years old, msd height, weight and bmi: 133.82.40 cm, 35.62.97 kg, and 19.91.21 kg/cm2), were selected and performed the tests in three stages (fast music, slow music, control) with counter balance method. in each stage, the...

Background and Objectives: Given the limited number of studies on Ramadan fasting and military performance, we conducted this study to identify the effect of Ramadan fasting on physical fitness performances in army cadets. Methods: Twenty healthy males were randomly selected from a larger sample group. The subjects were divided into fasting (n=10) and non-fasting (n=10) groups. They performed v...

The combination of push and pull information retrieval technology can benefit from collaborative information gathering schemes. In this paper we outline an approach that combines a pull technology (Knowledge Brokers) with a push technology (Knowledge Pump) in a community-based environment. Appropriate toolkits supporting synchronous collaboration on the World Wide Web are briefly introduced. A ...

While many techniques use the traditional approach of time consuming groundtruthing large amounts of data [1, 2], this is increasingly infeasible as dataset size and complexity increase. Instead we propose a solution that allows the user to select media that semantically belongs to the same class and use machine learning to “pull” this and other related content together. We use real data harves...