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Data security, complete system control, and missed storage and computing opportunities in personal portable devices are some of the major limitations of the centralized cloud environment. Among these limitations, security is a prime concern due to potential unauthorized access to private data. Biometrics, in particular, is considered sensitive data, and its usage is subject to the privacy protection law. To address this issue, a multimodal authentication system using encrypted biometrics for the edge-centric cloud environment is proposed in this study. Personal portable devices are utilized for encrypting biometrics in the proposed system, which optimizes the use of resources and tackles another limitation of the cloud environment. Biometrics is encrypted using a new method. In the proposed system, the edges transmit the encrypted speech and face for processing in the cloud. The cloud then decrypts the biometrics and performs authentication to confirm the identity of an individual. The model for speech authentication is based on two types of features, namely, Mel-frequency cepstral coefficients and perceptual linear prediction coefficients. The model for face authentication is implemented by determining the eigenfaces. The final decision about the identity of a user is based on majority voting. Experimental results show that the new encryption method can reliably hide the identity of an individual and accurately decrypt the biometrics, which is vital for errorless authentication.

This paper addresses the notion of the impact of mobile learning technology from the learner's as well as educator's point of view. The authors have outlined the application of the e-learning in smart classes, which is followed by a similar argument with regard to the m-learning technology. This is followed by a statistical evaluation of the m-learning which through multiple surveys is conducted among the undergraduate and postgraduate students as well as the academics. In conclusion, the outcomes of these surveys are presented in graphical forms that highlight the merits and demerits of the m-learning technology.

In todays advanced technology environment, we come across a number of research areas that require extensive data processing. These areas include but not limited to, modeling and simulation of accuracy, safety and reliability of nuclear weapons, global warming, weather forecasting, DNA computing, nanotechnology, immune cell system, optical computing. Since we constantly continue to explore new avenues in our research program, hence the demand for improvements in other scientific and engineering parameters are continuously on the rise. These scientific and engineering requirements include but not limited to speed, reliability, fault tolerance, availability, compatibility, scalability, flexibility, cost to name a few. In todays environment, utilisation of parallel processing not only satisfies increasing demand for extensive data processing, yet it relatively fulfils deficiencies that one would experience in these scientific and engineering requirements. To this effect the authors have introduced architectures based on Master-Slave Multi-Super-Hypercube DX-Tree architecture and Master-Slave Multi-Super- Hypercube Star Ring Architecture. For these architectures and the current message passing architectures, the total system costs are developed and through mathematical modeling and simulation are compared. In this comparison the merit and demerits of these architectures from the cost point of view are highlighted to enable the user to select an appropriate Message-Passing architecture which would best satisfy ones scientific requirements.

In recent years the area of High Performance Computing (HPC) has received an outstanding support both from the users as well as the computer system designers. This support is mainly due to the increase of the complexity and density of the data processing of some of the advanced research areas. These areas include but not limited to, the climate modeling, weather forecasting, and performance measurement and improving precision of the nuclear weapon systems as well as space programs. This rise in complexity would impose additional pressure on the clients to demand for further improvements on system features such as speed, reliability, performance, fault tolerance, compatibility, size and cost. This is one of the determining factors that encourages our researchers to model new architectures in the areas of HPC in order to satisfy the clients' scientific and engineering requirements. With this motivation in mind the author has introduced a new architecture which is coined as Master -Slave Multi-Super Hypercube DXTree architecture ((MS)2 HDX - T). For this architecture the total system cost through mathematical modeling and simulation is compared with similar parameters in the existing HPC systems. The result highlights the advantages or otherwise of the proposed architecture from scientific research and/or commercial point of view.

The main objective of this work is to design and construct a small multiple microprocessor system based on the cross-bar switch architecture. The motives behind this are twofold; firstly there seems to be great potential in the architecture, and secondly, few previous constructional projects employing this architecture have been reported. A system is presented employing three Z80 microprocessors in a master-slave configuration with a floppy disc based support system. The various design decisions are outlined, and an estimate is made of the reliability of the hardware. This work, in particular, has highlighted the flexibility and simplicity of the architecture, in addition to the obvious potential of high speed of operation. It is also found that parallel programs can easily map onto the system, though this is not dealt with here.