Abstract Parallelism is the concept that associates with participating more than one computer, process, or thread in one problem execution. The concept is used for increasing multitasks performance execution effectively. Many algorithms, techniques, architectures, frameworks, and environments are found to enhance this concept and finally enhance the performance. However, two basic environments are exists to execute parallel tasks; these two environments are Virtual and Physical... Parallelism is the concept that associates with participating more than one computer, process, or thread in one problem execution. The concept is used for increasing multitasks performance execution effectively. Many algorithms, techniques, architectures, frameworks, and environments are found to enhance this concept and finally enhance the performance. However, two basic environments are exists to execute parallel tasks; these two environments are Virtual and Physical parallelism. Both of these two runtime environments have their features, advantages and disadvantages. The paper focuses on analyze, evaluate and clarify some differences between the two environments. Results depend on real case study executed via Java-Thread, Open-MP, MPI in virtual environment and an MPI in physical environment. Implementation of the case study and validation results are shown and they clearly clarify the advantages, disadvantages and limits of using any environment of them. Read More Read Less

Abstract This paper investigates the effect of shifting roles of faculty in educational delivery in e-learning environments at the pre-teaching stage (the preparation stage before lecturing), teaching stage (during lectures) and post-teaching stages (after lecturing) in both private and public Universities in Ghana. Researches have shown that e-Learning has brought about a transformation in teaching and learning. The lecturer’s role is redefined from the... This paper investigates the effect of shifting roles of faculty in educational delivery in e-learning environments at the pre-teaching stage (the preparation stage before lecturing), teaching stage (during lectures) and post-teaching stages (after lecturing) in both private and public Universities in Ghana. Researches have shown that e-Learning has brought about a transformation in teaching and learning. The lecturer’s role is redefined from the possessor of knowledge to a facilitator who guides students to acquire knowledge. A sample of 300 lecturers out of 1,800 was drawn from both private and public universities in Ghana. Regression analysis was used to determine the nature of the relationship. A model was developed to establish a relationship between the variables. The research found that there is a strong relationship between the independent variables (overall role change) and the dependent variable (lecturer performance at the pre-teaching stage). A strong relationship between the performance of lecturers at the teaching stage and role change was also observed. However, there was no relationship between the performance of lecturers at the post-teaching stage and role change. The results show that lecturers’ role change influenced their performance positively at the pre-teaching and teaching stages only. Understanding the relationship between lecturer’s role change and their performance at the three stages due to adoption of e-learning, will enable lecturers position themselves to be effective lecturers despite the change in role. Read More Read Less

Abstract An enriching of stream data with disk-based master data is common in many applications. Real-time data warehousing is one of these applications where stream data is customers transactions producing by operational data source(s). This stream data needs to enrich by disk-based master data before loading this into the data warehouse. To implement this enrichment operation a join operator is required. Normally we call... An enriching of stream data with disk-based master data is common in many applications. Real-time data warehousing is one of these applications where stream data is customers transactions producing by operational data source(s). This stream data needs to enrich by disk-based master data before loading this into the data warehouse. To implement this enrichment operation a join operator is required. Normally we call it semi-stream join as it is performed between stream data and disk data. The join operator typically works under limited main memory and this memory is generally not large enough to hold the whole disk-based master data. Therefore, the relation is loaded into memory in partitions. A well-known join algorithm called MESHJOIN (Mesh Join) has been presented in the literature to implement the semistream join operation. However, the algorithm suffers with some limitations. In particular, the algorithm can be improved based on the characteristics of stream data e.g. skew in stream data. In this paper we address this issue by presenting a novel algorithm called Cached-based Stream-Disk Join (CSDJ). The algorithm exploits skew characteristic in stream data more appropriately and over performs existing MESHJOIN. We present results for Zip-fian distributions of the type that appear in many applications. We evaluate our algorithm using synthetic, TPC-H and real datasets. Our experiments show that CSDJ performs significantly better than MESHJOIN. Read More Read Less