This study examines capital adequacy and the moderating impact of asset growth on the performance of firms in the agricultural sector. 4 listed agricultural firms were examined over a period of 10 years and data were extracted from their financial statements which were analyzed through a STATA 13 tool of analysis. Regression, correlation matrix and descriptive methods of analysis were employed to present and analyze results. Other post estimation tests like skewness and kurtosis test, Variance Inflation Factor test, specification test, heteroskedasticity tests and hausman test to select between fixed effect and random effect regression model were conducted to ensure robustness of results. The fixed effect stochastic longitudinal regression analysis model was adopted as guided by the hausman test. From the findings posited by the study, liquidity structure, liquidity structure moderated by asset growth and the combined effect of firm size moderated by asset growth were found to be significantly impacting on return on asset of firms at 1% level of significance. Firm size was found not to have any significant impact on return on assets. It was therefore recommended that the management should ensure considerable excess of current assets over current liabilities at all times so that there will always be positive liquidity structure; management should ensure consistent and prudent capital acquisition to ensure larger firm size; management should ensure steady asset growth by asset revaluation and new acquisition over time; the regulatory authority in the agricultural sector should establish a firm size benchmark below which no firm should operate. 折りたたむ

In recent times, the urge to collect data and analyze it has grown. Time stamping a data set is an important part of the analysis and data mining as it can give information that is more useful. Different mining techniques have been designed for mining time-series data, sequential patterns for example seeks relationships between occurrences of sequential events and finds if there exist any specific order of the occurrences. Many Algorithms has been proposed to study this data type based on the apriori approach. In this paper we compare two basic sequential algorithms which are General Sequential algorithm (GSP) and Sequential PAttern Discovery using Equivalence classes (SPADE). These two algorithms are based on the Apriori algorithms. Experimental results have shown that SPADE consumes less time than GSP algorithm. 折りたたむ

The purpose of this essay is to discuss the advantages and disadvantages and the benefits and costs of Big Data. The paper outlines the relevant federal and state privacy laws, including the California Consumer Privacy Act as amended, the Virginia Consumer Data Protection Act, and the Colorado Privacy Act. While highlighting several Federal Trade Commission privacy violation cases, the effects of Big Data collection and government surveillance are described in some detail. Advertising and marketing are defined, where it is argued that while the scanning of emails by email providers may be legal, it should be accomplished with consent, or not at all. The essentials of contract law and specific contract negotiation techniques are outlined for the benefit of attorneys. Finally, it is argued that although Big Data is the wave of the future, like all human institutions, it has in its definition the inherent paradoxes of transparency, identity, power, and exclusion that may potentially spell its undoing. 折りたたむ