This paper considers a common problem that all industries contest with in practice ie the breaking down of machines that influence production and cost directly. In a majority of industrial applications, acquiring optimum utilisation of all available resources for existing and future predicted demand is a major function throughout all the levels of management. This paper uses a number of analytical tools and software that support one another ie Witness Simulation, Bayesian Network Modelling and Hugin Software. The use of expert experience and knowledge has been incorporated throughout the study as it is vital to model building and greater understanding of machine breakdown. This study uses discrete event simulation and Bayesian network modelling collectively to understand machine breakdowns to increase efficiency within a cement manufacturing plant ie the Crusher Machine. The Bayesian network modelling implemented by the Hugin Software is used to generate probabilities which are transferred into a discrete event simulation model using Witness Software based on the historical data, expert knowledge and opinions. The model simulates the three parameters of the machine life based on consumption of each parameter. This is translated into a probability failure rate that changes as the model is running. The model demonstrates decisions based on the probability of failure from the Bayesian model and based on life consumption of the different variables in the simulation model.

The aim was to build an educational website to teach preschoolers aged 2-5 years old some skills; related to reading, writing and pronouncing alphabet, numbers, animal names, shapes and other common words. Also, assist parents and teachers by providing digital game-based learning environment to “edutainment” the children. The study illustrated the usability and usefulness of this educational game-based website and provided future insights for researchers and developers to take into account in future work.

Libya as many other regions under arid climates suffer from inadequate water resources to cover all the needs of this rapidly developing country. Increasing water amounts for population supply, agricultural irrigation and use for industry are needed. As groundwater is the main water source in the country it represents a natural resource of the highest economic and social importance. FEFLOW numerical model was implemented in a regional scale to show how the natural situation has been changed after heavy groundwater abstraction having occurred in the last decades in the northwestern part of Libya. Results of the numerical model indicated that the current zones of depression in piezometric surface could have been caused by smaller withdrawn amounts than previously estimated. Indicated differences in assessed withdrawn groundwater volumes seem to be quite high and might influence considerably the future possibilities of groundwater use in the study region.

one of the challenges recently occurred in the concept of hiding data is the

robustness of hiding data in the way that is difficult to access or detect. Most of the steganography

schemes are based commonly on embed data within images or video frames on their original form

(uncompressed domain).

This paper presents a new methodology for data hiding in MPEG-2 video standard. Data will be

embedding during the compression stage of the AVI-MPEG2 encoding. The BPCS algorithm has

been modified and used in all our experiments for embed data, and the DES (Data Encryption

Standard) algorithm has been used to encrypt data before hiding. It only embeds encrypted data

bits in the quantized AC coefficients (low-frequency AC coefficients) of Y components (Luminance)

for the I-Frame. The obtained results demonstrate that the proposed method has the considerable

advantage over previous steganography schemes with a good PSNR values for the embedded