Blood banking is the process of collecting, separating and warehousing blood. There are numerous file-based repositories of blood bank management that exist for storing data for blood bank ecosystem such as hospitals and centers. This functions for maintaining the information of donors, availability of blood, and transaction information. Currently, these systems are effort intensive, costly, and failed to achieve efficiency in terms of its filtering mechanism which makes repository penetrating faster and reliable. This paper introduces a new design for blood banking ecosystem with proper filtering solution using frame-based approach. The system has three major features: (1) blood camp setup module, (2) stocks management module which includes the blood donation and blood releasing, and (3) the filtering system module which shows the nearest blood camp with the available blood type based on the patients’ needs. Also, with the use of frame-based approach as filtering method, the system is more efficient and reliable compared to other blood banking repository systems. The system’s functionality was tested for its efficiency, usability, and reliability and the results are revealed in the survey. Conclusions and future work were also provided in this paper.

The blockchain phenomena is no longer about Bitcoin or cryptocurrency, it is beyond a common protocol to make it nearly impossible to create fraudulent transaction. Blockchain based architecture overall performance is subjected to storage expenses with high computational cost. This paper designed a new consensus protocol for Blockchain using Content Addressable Pattern with the adaptation of modified SHA256 algorithm. Although government, business and other entities interest of adapting blockchain to their processes, the complexity issues and operational cost is still a challenge to date. With the newly design consensus protocol the process of validating the transaction that involves tedious mining or solving cryptographic puzzles has been eliminated and move towards using signature to authenticate the transaction. Concatenation of all these elements is a generated hash value using modified SHA256. Since the hash is secured, the transaction is secured. Thus, the implementation of off-chain chanel instead of global consensus addresses the complexity and high computational cost of blockchain technology.

Data analysis is an integral part of research. Most researchers examine their results by using graphs, tables, charts, and figures. These methods are effective, but knowledge transfer is limited because it only depends on what the authors or researchers have presented. The need to scrutinise further the given data is essential. One way of addressing this problem is to utilise a graphical user interface (GUI), wherein a user can manually choose some parameters of an extensive dataset to display and analyse. In this paper, the results of the four variants of clustering techniques, namely the Ant Colony Optimization (ACO), Gaussian Mixture Model (GMM), K-Power Means (KPM), and Kernel-Power Density-Based Estimation (KPD), in grouping the wireless multipath propagations, are evaluated through the use of a GUI. The accuracy performance of each clustering algorithm can be obtained by choosing in the GUI the corresponding channel scenario that the user would like to investigate. A deeper analysis of the clustering characteristics can also be done by selecting other parameters in the GUI. This selection gives a better understanding of the behaviour of each clustering technique and provides an effective way of presenting and analysing the different sets of data.