The smart household connected to the energy dispatch arises to overcome the environmental crisis, encourages the penetration of renewable energies and promotes consumer respond to intraday market prices. Aquaponic production results from the combination of fish farming and hydroponics (cultivating plants using fish waste as nutrients). The prototype was built based on the rule of the 3 Rs: reduce, reuse and recycle. The crop reduces the consumption of water and energy, reuses water in a recirculation process, which is filtered by: 1) gravity, 2) biofilters and 3) porosity. Recycling is expanded to plastic containers and food containers of polystyrene. The aquaponic production system is decorative, completely organic (without chemicals), promotes the growth of green areas for comfortable homes and allows the consumption of healthy food, as well as energy planning to save energy. The system is done with a digital level control connected to a water pump and an oxygen pump. A novel method allows the aggregator to optimize the recirculation programming of the aquaponic system for periods of 24 hours. The method maximizes the economic benefits with the help of an energy balance between hours.

This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter. This is a quite common condition for high-speed low-resolution converters. A digitized sine wave is transformed into the frequency domain through the discrete Fourier transform. The error in the amplitude estimate is treated as a random variable since the offset and the phase of the sine wave are usually unknown. Therefore, the estimate is characterized by its standard deviation. The proposed model evaluates properly such a standard deviation by treating the quantization with a Fourier series approach. On the other hand, it is shown that the conventional noise model of quantization would lead to a large underestimation of the error standard deviation. The effects of measurement parameters, such as the number of samples and a kind of the time window, are also investigated. Finally, a threshold for the additive noise is provided as the boundary for validity of the two quantization models

The paper present the concept of stability assessing the of solutions which are construction schedules. Rank have been obtained through the use of task scheduling rules and the application of the KASS software. The aim of the work is the choice of the equivalent solution in terms of the total time of the project. The selected solution optimization task should be characterized by the highest resistance to harmful environmental risk factors. To asses the stability of schedule simulation technique was used.

The article describes the finds of six Roman coins and a mysterious object with an Arabic legend discovered in the years 2000–2014 at the bottom of Lake Turawskie, created in 1939. With the creation of the reservoir many archaeological sites (of varied chronology, from the Roman period to the late Middle Ages) were flooded, many of which could not be properly investigated due to the time pressure. The Roman coins presented here are a standard part in the overall image of coins discovered in Silesia. The mysterious object with an Arabic legend is unique, it has partial analogies in Norman weights or early-Arab coins (al-wafā lillāh coinage).

The aim of the study was to choose and validate the tool(s) to predict the number of hospitalized patients by testing three predictive algorithms: a linear regression model, Auto-Regressive Moving Average (ARMA) model, and Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model. The study used data from the collection of data on infl ammatory bowel diseases (IBD) from the public database of the National Health Fund for the years 2009–2017, data recalculation taking into account the population of provinces and the country in particular years, and prediction making for the number of patients who would require hospitalization in 2017. Th e anticipated numbers were compared with real data and percentage prediction errors were calculated. Results of prediction for 2017 indicated the number of hospitalizations for Crohn’s disease (CD) and ulcerative colitis (UC) at 17 and 16 respectively per 100,000 persons and 72 per 100,000 persons for all IBD cases. Th e actual outcomes were 21 for both CD and UC (81% and 75% accuracy of prediction, respectively), and 99 for all IBD cases (73% accuracy). The prediction results do not diff er signifi cantly from the actual outcome, this means that the prediction tool (in the form of a linear regression) actually gives good results. Our study showed that the newly developed tool may be used to predict with good enough accuracy the number of patients hospitalized due to IBD in order to organize appropriate therapeutic resources.

The author recalls the profiles of some selected Polish scientists and their achievements in context of the current situation of Polish science.