Encyklopedia rachunkowości / The Accounting Encyclopedia

This is an encyclopedia of accounting terms

Analysis of thermal properties of coffee grounds left over from coffee percolation

Coffee is one of the most popular beverages worldwide. The goal of this work is an estimation of the qualities of waste coffee grounds as a material used in biofuel production. There were selected two most popular coffee beans mixtures: arabica and arabica with robusta, as well as chocolate-flavoured coffee and green coffee (unroasted coffee beans). All types of coffee had approximately the same ash value its average oscillating between 2,59-3,21%. Calorific value of the dried waste coffee grounds after coffee percolation places it among very good energy material

Research on Determination of Water Diffusion Coefficient in Single Particles of Wood Biomass Dried Using Convective Drying Method

Determination of the mass diffusion coefficient for dried, inhomogeneous material is difficult as it depends on the drying agent temperature and the moisture content and physical structure of the material. The paper presents a method for efficient determination of the water diffusion coefficient for wood solid cuboids dried using convective drying methods. In this work, the authors define a theoretical dependence of the Fourier number on reduced water content in a convectively dried cuboidal solid, based on a simplified theoretical solution of the diffusion equation for such a body. The material for drying included shoots of common osier, robinia (false acacia), multiflora rose, and energy poplar, dried at temperatures of 40, 50, 60, 70, and 80 °C, in free convection. The obtained results differ from the theoretically anticipated changes of the coefficient

The impact of mechanical pre-treatment of wood biomasson drying rate

The work presents the process of drying wood biomass after pre-treatment involving either debarkingor crushing. The biomass used for research came from a robinia species wood. The material was driedin free-convection, at the drying medium temperatures of 40, 50, 60, 70 and80◦C, respectively. Pre-treatment proved to have a significant impact on the drying rate, including the time required to reachmoisture content of 10%, essential to start further treatment of biomass for power industry purposes.It was found that debarked samples of robinia lost water more quickly than the crushed ones. Samplesthat did not undergo pre-treatment took the longest time to dry

System ekspertowy wspomagający podejmowanie decyzji w procesie zwalczania szkodników warzyw w okresie wegetacji

The paper presents a computer system supporting the identification of vegetable pests during the vegetation period and the way in which it works on the example of red beet. The objective was to develop an expert system to facilitate the identification of pests and suggest an appropriate method of controlling them. Filling the database with the knowledge applying to one narrow area of knowledge turns the expert system framework into an expert system in this area of knowledge. The system consists of the expert system and the database in the form of text files, which contain additional explanations. The user of the expert system - “DSS - pest control” needs to answer the following questions: in the first stage the user selects the diagnosed vegetable, in the second stage, the user selects the symptom or symptoms on the above-ground vegetable part, in the third stage, the user selects the symptom or symptoms on the below-ground vegetable part. The designed decision support system (“DSS - pest control”) may be used by individual vegetable growers. It may also serve as an educational program, e.g. for students who want to find out more about the specific areas of knowledge as well as for scientists and researchers.Artykuł przedstawia system komputerowy wspomagający identyfikację szkodników warzyw podczas procesu wegetacji, a także sposób jego działania na przykładzie buraka czerwonego. Celem było opracowanie systemu ekspertowego ułatwiającego identyfikację szkodników oraz zaproponowanie odpowiedniej metody ich zwalczania. Wypełnienie bazy wiedzy informacjami odnoszącymi się do wąskiego obszaru wiedzy zamienia system ekspertowy w system w danej dziedzinie wiedzy. System składa się z systemu ekspertowego oraz bazy danych w postaci plików tekstowych, które zawierają dodatkowe wyjaśnienia. Użytkownik systemu ekspertowego - "DSS - zwalczanie szkodników" musi odpowiedzieć na następujące pytania: w pierwszym etapie użytkownik wybiera diagnozowane warzywo, w drugim etapie użytkownik wybiera objaw lub objawy na nadziemnej części warzywa, w trzecim etapie użytkownik wybiera objaw lub objawy na podziemnej części warzywa. Zaprojektowany system wspomagania decyzji ("DSS - zwalczanie szkodników") może być stosowany przez indywidualnych plantatorów warzyw. Może również służyć jako program edukacyjny, np. dla studentów, którzy chcą pogłębić swoją wiedzę, może być także pomocny dla naukowców i badaczy

The Use of Brewer’s Spent Grain after Beer Production for Energy Purposes

The aim of this study was to assess the possibilities to use brewer’s spent grains (BSGs) left over from beer production for energy purposes, and to determine its calorific value and chemical composition. The research materials were samples of wet spent grain from a brewery in Poland. Three samples, that are different in ingredient composition, were examined. The examined samples of BSGs were characterised by humidity that is typical for this product (approx. 77–80%). Convective drying of the spent grain contributed to a reduction in the water content in the biomass to below 10%. Samples of dry spent grain that were examined contained a similar amount of ash (3.8–4.1% d.m.) and organic matter (91.0–91.9% d.m.). All the examined spent grain samples demonstrated similar volatile matter content—approx. 77.8–78.7% d.m. and calorific value—approx. 15.6–15.9 MJ/kg. The estimated calorific value for wet samples (approx. 1.4–2.0 MJ/kg) indicated that it is necessary to lower water content in the biomass in order to improve its energy properties

An Approach to Assessing the State of Organic Waste Generation in Community Households Based on Associative Learning

The purpose of this work is to substantiate the approach to assessing the state of organic waste generation by households of a given community, which is based on passive production observations and intellectual analysis of statistical data, which ensures consideration of the factors and features of organic waste generation, as well as the development of qualitative models for forecasting their receipt. To achieve the goal, the following tasks were solved: the analysis of the state of organic waste generation by households in the EU countries was performed; an approach to assessing the state of organic waste generation by households of a given community is proposed; based on the use of the proposed approach, and models for assessing the state of organic waste generation of households in a given community were substantiated. The hypothesis of the study is to substantiate and use an approach to assessing the generation of organic waste by households in individual communities, based on the method of association learning and search for association rules, which will identify factors that have a significant impact on the volume of organic waste generated by households, the consideration of which will improve the accuracy of forecasting models and improve the quality of management of the processes of collection and processing of this waste in communities. The research methodology used allows for the use of data mining, probability theory, mathematical statistics, machine learning technology, and the Associative Rule Learning (ARL) method. Based on the use of a reasonable algorithm, they identify key trends and relationships between the factors of organic waste generation in communities in different countries, which is the basis for creating accurate models for predicting the volume of collection and processing of this waste in communities. The study found that the largest number of households produced organic waste per capita in the range of 0.14–0.25 kg/person. At the same time, most households have from two to four residents and are located on the adjoining territory from 350 m2 to 680 m2. Based on the method of learning associative rules, it was found that there are no close correlations between individual factors that determine the daily volume of organic waste generation by households per capita. The highest correlation coefficient between the type of housing and the income level of household residents is 0.13. The number of residents and the occupied area of the adjacent territory have the greatest impact on the daily volume of organic waste generated by households per capita. The substantiated associative rules of relationships, as well as the diagrams of relationships between factors, have helped to identify those factors that have the greatest impact on the volume of organic waste generation. They are the basis for creating accurate models for predicting the volume of collection and planning the processing of this waste in communities. Based on the proposed approach, Python 3.9 software was developed. It makes it possible to quickly carry out calculations and perform a quantitative assessment of the state of organic waste generation by households of a given community according to the specified rules of association between the volumes of organic waste generation and their factors. The results of the study are the basis for the further development of models for accurate forecasting of the collection and planning of the processing of organic waste from households in communities