Constructing an Algorithm for Selecting the Number of Histogram Bins in Statistical Hypothesis Testing for Normal Distribution of Sample Data
Abstract— Practice, on the whole, makes extensive use of the vast range of assumptions and conjectures in regards to the type of frequency distribution in statistical samples, the deviations from which would significantly affect the qualities of the model and the estimation accuracy of its parameters. Regrettably, a reliable and clearly defined criterion as to their permissibility is completely absent.
For instance the fish stock assessment procedure is initially based on assumption that the frequencies in the length-frequency samples used for estimation of growth parameters of fish and analysis of the stock status are normally distributed or follow approximately the normal distribution [15,17].
The purpose of the present study is to construct an algorithm for identification of the statistical distribution of a random variable focusing on the proper selection of the number of histogram bins and further assessment of its impact on the stochastic models delivered. To that effect, appropriate simulation studies have been carried out to compensate for the lack of any concrete evidence related to the potential impact of the number of bins in the histogram and the overall data accuracy on the results of the application of the statistical criterion for the verification of the law of distribution. Applied has been the direct statistical method for determining the law of the distribution – chi-square criteria along with some indirect methods. Provided for the simulation studies were machine-generated data sets and the relevant simulations were held in MATLAB programming environment.
Abstract – The present article describes the experimental measurements of thermal resistance of the PUR insulation installed in the selected type of hot water heaters that are necessary for the purpose of identification of heat output or heat loss in the given heater.
Abstract – The process of heat distribution through heat networks is accompanied with significant loss. That is why distributors of heat and hot water are nowadays very interested in these issues. The drawbacks of the existing methods of heal loss calculation brought the necessity of searching new procedures of such calculation.
The article presents a possibility of using the similarity theory and modelling in order to transpose results from an experimental heat network to any other network that will be similar to the experimental network with regard geometry, kinematics, as well as heat parameters.
Material Conversion of Waste Aluminoborosilicate Glass into Faujasite-type Zeolite using Alkali Fusion
Abstract—A large amount of liquid crystal display (LCD) television becomes popular for the last decades, and the amount of waste LCD panels will increase soon. LCD panels mainly consist of aluminoborosilicate glass, and it is difficult to recycle aluminoborosilicate glass using the same recycling method of soda-lime glass, due to the high strain point. Therefore, a novel recycling method for aluminoborosilicate is desired. In this study, we attempted to convert waste aluminoborosilicate glass powder into faujasite-type zeolite using alkali fusion method. Waste aluminoborosilicate glass powder (< 300 μm) were mixed with NaOH powder (the weight ratio of NaOH / aluminoborosilicate = 1.0 – 2.0), and then heated at 100 – 800 oC for 0.5 – 7 h to make a fused material with high solubility. This fused material was agitated in distilled water for one day, then heated at 80 oC for 24 hours to synthesize zeolite product. Most of the aluminoborosilicate glass were converted into soluble phases by alkali fusion with NaOH (NaOH / sample = 1.5) at 400 oC for 0.5 h, and could be transformed into faujasite-type zeolite. The cation exchange capacity (CEC) of the zeolite product is 1.9 mmol/g, which is 31 times higher than that of raw glass powder, and is 59% of CEC for commercial faujasite-type zeolite 13X (3.2 mmol/g). Zeolitization process from agitated material can be explained by theconcentrations of Si, Al and B in the product and the crystallinity of faujasite-typezeolite in the product.
Abstract— The management of the living marine resources (stocks) exploitation entails the pursuit of a science-based policy in order to preserve the reproductive capacity of the stocks and their sustainable development in the course of time i.e. maintaining the stocks biomass levels within safe biological limits [27,28].
The excessive increase in catches (fishing effort) due to unscrupulous exploitation can result in irreversibly collapsed biological basis for their existence [19,27,28]. The situation thus created is further exacerbated by the incomplete or poor-quality information about the development of the stocks potential. The present paper advances the adoption of cybernetic approach to the analysis of the management and exploitation of the living marine resources. Proposed also is a block diagram of the stock management system in a context of uncertainty and the use of the precautionary approach and step algorithm for the collection, analysis, processing of information and evaluation of the parameters and the reference biological indicators of the respective biological objects, on the basis of which the target (the target management indicator) is to be set.