Dairy wastewater generally contains fats, lactose, whey proteins, and nutrients. Casein precipitation causes the effluent to decompose into a dark, strong-smelling sludge. Fluid waste contains soluble organic matter, suspended solids, and gaseous organic matter, which cause undesirable taste and smell, grant tone and turbidity, and advance eutrophication, which plays an essential role in increasing biological oxygen demand (BOD) in water. It also contains detergents and disinfecting agents from the rinses and washing processes, which increase the need for chemical oxygen (COD). One of the characteristics of dairy effluents is their relatively high temperature, high organic contents, and wide pH range, so the discharge of wastewater into

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic

This research aims to develop transdermal patches of Ondansetron hydrochloride (OSH) with different types of polymers, ethyl cellulose and, polyvinyl pyrrolidone k30 in a ratio (3:0.5,3:1,3:2,2:1,1:1) with propylene glycol 20%w/w as a plasticizer. Prepared transdermal patches were evaluated for physical properties. The compatibility between the drug and excipients was studied by Differential scanning calorimetry (DSC), where there is no interaction between the drug and polymers. From the statistical study, there is a statistical difference between all the prepared formulations p<0.05. In-vitro Release study of transdermal patches was performed by using a paddle over the disc. The release profile of OSH follow

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin