Engineering Sector

Mobile services are becoming increasingly commonplace in everyday life; however, Mobile payment (M-payment) is not among frequently used mobile services. The slowness of the diffusion of this service is the point of departure of the current research. The authors discuss why consumers are slow in adopting M-payment service and develop a proposed model that measures the customer’s attitude and intention to use this technology in Egypt. Different theories from diverse fields are reviewed to formulate the study’s conceptual framework. Empirical data were collected via an online survey for a sample of 490 students in “open education”, a type of e-distance learning. The results suggest that although the most important determinants influencing the customer’s attitude toward the service are perceived behavioral control and perceived usefulness, those influencing the intention to use it are perceived innovativeness, perceived expressiveness, facilitating condition, perceived usefulness, and social pressure. The results of the research differ from those of previous studies because of the effect of the Egyptian culture. Service providers can benefit from the results when formulating the marketing strategies to increase the usage of this service, improving mobile commerce.

Feature selection (FS) is a key step in the data mining process. In FS, the objective is to select the smallest subset of features that reduces complexity and ensures generalization. In this paper, we present a combined filter-wrapper feature selection approach using misclassified data.

Effective task scheduling is essential for obtaining high performance in Heterogeneous Distributed Computing Systems (HeDCSs). However, finding an effective task scheduling in HeDCSs should take into consideration the heterogeneity of processors and inter-processor communication over head, which results from non-trivial data movement between tasks scheduled on different processors. In this paper, a new high performance task scheduling algorithm called Sorted Nodes in Leveled DAG Division (SNLDD) is presented for HeDCSs with considering a bounded number of processors. The main concept of the proposed algorithm is to divide the Directed Acyclic Graph DAG into levels and tasks in each level are sorted in descending order according to their computation size. A new attribute has been introduced and used to efficiently select tasks for scheduling in HeDCSs. This selection of tasks enables the proposed SNLDD algorithm to generate high-quality task schedule in a heterogeneous computing environment. To evaluate the performance of the proposed SNLDD algorithm, a comparison study has been done between it and the Longest Dynamic Critical Path (LDCP) algorithm which is considered the most efficient algorithm. According the comparative results, it is found that the performance of the proposed algorithm provides better performance than the LDCP algorithm in terms of speedup, efficiency, complexity, and quality.

The authors establish some new criteria for the oscillation of solutions of fourth order nonlinear neutral delay dynamic equations of the form a(t) (x(t) - p(t) x (t (t)))???) ? + q (t) x? (g(t)) = 0