A new continuous numerical approach based on the approximation of polynomials is here proposed for solving the equation arising from heat transfer along a large flat steel plate subject to initial and boundary conditions. The method results from discretization of the heat equation which leads to the production of a system of algebraic equations. By solving the system of algebraic equations we obtain the problem approximate solutions.

Hourly global and diffuse irradiance data are used to estimate Linke turbidity factor (TL ) at two sites in Cyprus, representing two different climate regimes of the island (Athalassa-inland plain vs Larnaca-coastal location) for the period January 2013-December 2015. The annual mean values of TL are 3.40 at both stations. The daily and monthly variation of atmospheric turbidity has been studied. It was found that atmospheric turbidity decreases during the winter season (rainy season) and increases during the summer season. The higher diurnal variation is observed in spring and summer months at both stations. TL is increased from morning to afternoon. The increase of TL from morning to afternoon can be attributed to the fact that higher traffic activities are observed during the day at both stations. The results presented are comparable to those recorded in different places in Mediterranean region. The Cumulative Frequency Distributions (CDF) of TL shows that about 37% of TL values are less than 3, 50% are between 3 to 5 and only 13% are greater than 5. This indicates that the skies on cloudless days are clean and clear. The short-term variation of atmospheric turbidity depends on local weather conditions (temperature, vapour pressure, wind speed and wind direction) and its long-term one on the climate of the area. It was found that the Linke turbidity factor is increased linearly with air temperature at both stations. TL is also increased with increasing the vapour pressure at both stations. The prevailing winds, which may transport moisture or aerosol particles from distant sources, play a major role in the spatio-temporal variation of turbidity. Wind speed also plays a significant role in the transport of moisture or aerosol particles. The diffuse irradiance is increased with the increase of atmospheric turbidity. Linear relationships were established between diffuse irradiance and atmospheric turbidity. Comparing TL values of different locations over the island, it was found that the high altitude station has the lowest values, since this station has clearer atmosphere than the other sites.

The study objective is to establish an interactive Big Data Platform Analytics (BDA) platform with Hadoop/ MapReduce technologies distributed over HBase (key-value NoSQL database storage) and to generate hospitalization metadata on the platform. Performance tests retrieved results from simulated patient records with Apache tools in Hadoop’s ecosystem. At optimized iteration, the Hadoop distributed file system (HDFS) ingestion with HBase exhibited sustained database integrity over hundreds of iterations; however, the platform required a month to complete its bulk loading via MapReduce to HBase and validate queries required a month. To generate HBase datafiles, the framework took a week for one billion (10TB) files and a month for three billion (30TB) files. Inconsistencies of MapReduce limited the capacity to generate/replicate data efficiently. Dependencies among the data elements system could be expressed via “family” primary keys set in code via Apache Phoenix as database generator. Modeling a hospital system based on a patient encounter-centric database was very difficult because data profiles were fully representative of complex relationships. Apache Spark and Apache Drill showed high performance. Recommendations regarding key-value storage should be considered when analyzing large volumes of healthcare data securely.

Object Oriented Bayesian Networks (OOBNs) are a semi-quantitative modeling approach that can be utilized to represent complexities of management tradeoffs and spillovers within a conservation and ecological context. However, computation expense and gradual learning curve result in their underutilization in ecological and environmental disciplines. This is despite the reoccurring need for decision-makers to adapt wildlife management protocols while constraint by limited resources and scarce data. We provide guidelines to identifying and prioritizing uncertainties surrounding complex ecological processes. Empirical data and expert explicit understanding of uncertainties are utilized. We put forth two OOBNs, each accurately representing a snapshot of the moving parts in the complex wildebeest hybridization conservation case study in South Africa. We identifying and clustered key variables impacting the probability of hybridization in either spatial, biological, or market domains. Specifically, (i) blue wildebeest male to black wildebeest male ratio, and (ii) spatial connectivity. Ecologists facing similar constraints worldwide may utilize our stepwise procedural framework so that resources are maximized. This study promotes global collegially research by bridging the boundaries of applications across disciplines, so that their advantages may be extrapolated. The construction of the suggested prototypes is explained in detail so that they may be adapted modified to quantify similar ecology-related uncertainties worldwide.

Slutsky’s Theorem has important applications in biostatistics. Several generalizations of Slutsky’s Theorem are presented. For instance, we study the limiting distribution of n n Y X / when 0 n X→ in distribution. Then the sequence of random varibles tends to an extended random variable