Measuring Access to Continuing Professional Education among the Health Workers in Ghana: Constructing an Index

To measure the levels of access to continuing professional education (CPE) among the health workers, an index (continuing professional education access index: CEAI) was constructed. The CEAI is composed of six indicators: (i) availability of CPE; (ii) distribution of CPE; (iii) informational access; (iv) geographical access; (v) economic access; and (vi) preparedness to release staff. When developing the equation of the CEAI, these six component indicators were weighted in accordance with the order of importance reported by the earlier studies. To test its validity, the CEAI was applied to the CPE status in three regions of Ghana. The results of this application revealed that there was greater discrepancies in the CEAI values according to the type of health facilities. The type of health facilities with the greatest CEAI (= 0.609) implying the best access to CPE was clinics while training/research institutes resulted in the lowest CEAI (= 0.447). Regional variation among the three regions was not significant. A simple linear regression between CEAI and adjusted number of CPE opportunities per health worker produced an extremely high conformity in the model (R² = 0.960). This may indicate the validity of the proposed CEAI model to the large extent.     

A self-stabilizing 3-approximation for the maximum leaf spanning tree problem in arbitrary networks

The maximum leaf spanning tree (MLST) is a good candidate for constructing a virtual backbone in self-organized multihop wireless networks, but is practically intractable (NP-complete). Self-stabilization is a general technique that permits to recover from catastrophic transient failures in self-organized networks without human intervention. We propose a fully distributed self-stabilizing approximation algorithm for the MLST problem in arbitrary topology networks. Our algorithm is the first self-stabilizing protocol that is specifically designed to approximate an MLST. It builds a solution whose number of leaves is at least 1/3 of the maximum possible in arbitrary graphs. The time complexity of our algorithm is O(n ²) rounds.