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Wastewater treatment is a problem known to humankind for centuries. The quality of treated sewage determines the condition of reservoirs around the world. Control of such a complex and nonlinear system as a wastewater treatment plant requires thorough knowledge of the process. The paper presents a hierarchical control system of a Sequencing Batch Reactor (SBR) in Wastewater Treatment Plant (WWTP) taking into account a model based on actual measurements taken from a WWTP in Swarzewo, Poland. The authors designed and implemented a nonlinear model predictive controller (MPC) that allows for the optimal implementation of the desired DO level while minimising the operation of actuators (aeration system). The design description of the predictive controller was associated with the need to specify the performance function and define the optimisation problem. In a two-layer structure, a supervisory controller was implemented based on an actual time-based controller in Swarzewo WWTP. The overview showed the improved performance of the treatment plant and the versatility of the created solution. Results of simulation tests for the wastewater treatment plant case study are presented. • Dissolved oxygen control is very important for WWTP energy efficiency. • The process of designing a hierarchical control system of a SBR has been presented. • Nonlinear MPC has been applied for optimal implementation of the set DO trajectory. • Results of simulation tests for WWTP case study have been presented. [ABSTRACT FROM AUTHOR]

The friction pair formed by wheel and rail is subject to adhesive wear, which leads to a waste of time and money. The wear is inevitable but can be slowed down with the proper design of the wheel profile. This paper formalises the problem of automatic wheel profile design as a constrained optimisation and presents an efficient method of solving it using a state-of-the-art biologically-inspired black-box optimisation algorithm. The algorithm is multi-objective, in that it optimises not only the wheel and rail wear but also ride safety. The optimisation was performed for rail conditions in the city of Poznań, Poland. The performed simulations show that profiles obtained that way significantly outperform the ones currently used in Poznań in terms of wear index and derailment coefficient, which makes the new solution worth verifying experimentally and possibly putting into operation. Image 1 • A multibody simulation-based wheel profile optimisation algorithm was proposed. • Covariance Matrix Adaptation Evolution Strategy was used to develop the algorithm. • Track irregularities and vehicle structure were taken into consideration. • The new wheel profile achieved a better wear index and derailment coefficient. [ABSTRACT FROM AUTHOR]

ABSTRACT Most satellite cloud climatologies come in the form of global, low-resolution datasets: so- called 'gridded' Level 3 products, resulting from the reprojection and spatio-temporal aggregation of swath (Level 2) data. Their coarse resolution means that global datasets are of limited usefulness in regional studies. In this paper we develop and evaluate a new, regional cloud climatology over Poland and its neighbouring countries (∼10% of the area covered by Europe), based on observations performed with the state-of-the-art cloud imager, the moderate resolution imaging spectroradiometer ( MODIS). In contrast to the operational, global MODIS cloud climatology, which is delivered as a Level 3 product at a spatial resolution of 1° × 1°, this regional climatology maintains the MODIS nadir spatial resolution of 1 km/pixel. The resulting high-spatial-resolution climatology is compared with AVHRR and SEVIRI datasets, and surface-based ( SYNOP) observations at the level of monthly and annual means. The results shows that the standard MODIS Level 2 cloud mask product MOD35/ MYD35 can be successfully used to develop a regional, high-resolution cloud climatology. MODIS provides reliable estimates of cloud amount at the national scale (annual mean: 64.0% or 70.8%, depending on the MODIS data interpretation scheme), and correctly reproduces the annual cloud amount cycle (correlation between monthly means with SEVIRI/ AVHRR >0.98). A comparison with monthly mean surface observations reveals a bias ranging from −1.1% up to 5.9%, and a root mean square error of 4.2% − 6.6%. MODIS data also correctly indicates the spatial distribution of clouds. However, local anomalies were detected that were identified as artifacts of the MODIS cloud detection algorithm. Those artifacts covered 9% of the study area, but had no impact on spatially-averaged metrics. [ABSTRACT FROM AUTHOR]

The paper presents the complete design processes of novel aeration control systems in the SBR (sequencing batch reactor) wastewater treatment plant (WWTP). Due to large energy expense and a high influence on biological processes, the aeration system plays a key role in WWTP operation. The paper considers the aeration system for a biological WWTP located in the northeast of Poland. This system consists of blowers, the main collector pipeline, three aeration lines with different diameters and lengths, and diffusers. Classical control systems applied for this type of installation are based on PID (proportional–integral–derivative) controllers, the settings of which are often found experimentally. The article presents the optimization of these settings and the design of an alternative control algorithm—the fuzzy controller. [ABSTRACT FROM AUTHOR]

Despite the fact that sport plays a substantial role in people's lives, funding varies significantly from one discipline to another. For example, in Poland, women's basketball in the lower divisions, is primarily developing thanks to enthusiasts. The aim of the work was to design and implement a system for analyzing match protocols containing data about the match. Particular attention was devoted to the course of the game, i.e., the order of scoring points. This type of data is not typically stored on the official websites of basketball associations but is significant from the point of view of coaches. The obtained data can be utilized to analyze the team's game during the season, the quality of players, etc. In terms of obtaining data from match protocols, a dedicated algorithm for identifying the table was used, while a neural network was utilized to recognize the numbers (with 70% accuracy). The conducted research has shown the proposed system is well suited for data acquisition based on match protocols what implies the possibility of increasing the availability of data on the games. This will allow the development of this sport discipline. Obtained conclusions can be generalized to other disciplines, where the games are recorded in paper form. [ABSTRACT FROM AUTHOR]

This paper describes an application of an evolutionary algorithm and an artificial immune systems to solve a problem of scheduling an optimal route for waste disposal garbage trucks in its daily operation. Problem of an optimisation is formulated and solved using both methods. The results are presented for an area in one of the Polish cities. [ABSTRACT FROM AUTHOR]

In our paper, we compile a detailed 3-D velocity model of the crust for the territory of Poland and investigate the effect of a 3-D density distribution in the crust on geoid undulations. The major tectonic feature in the study area is the Trans European Suture Zone (TESZ) separating the Precambrian East European Craton from younger tectonic units of Palaeozoic Europe. High-resolution seismic models of the crust and upper mantle from recent controlled-source experiments were interpolated into a 3-D P-wave velocity model for the whole Poland. The model was converted to a density model assuming different equations connecting seismic velocities to densities for crustal rocks, sediments and the uppermost mantle. The crustal density model was used to calculate synthetic geoid undulations for the territory of Poland and to estimate influence of separate layers (topography, sediments, crust and uppermost mantle) on the geoid. To calculate the gravity effect of a large-scale 3-D density model, we developed a code based on a point mass algorithm as well as prisms algorithm that uses some easy to implement optimizations. The synthetic geoid undulations were compared to an existing gravimetric quasi-geoid solution. The modelling showed that the difference in crustal structure between the East European Platform and Palaeozoic Platform explains significant part of the observed geoid undulations in the study area. The remained residual could be related to density inhomogeneities in the upper mantle. [ABSTRACT FROM AUTHOR]

This paper presents the application of data mining algorithms to the prediction of Web performance. Our domain-driven data mining uses historic HTTP transactions data reflecting Web performance as perceived by the end-users located in the Internet domain of Wroclaw University of Technology, Wroclaw, Poland. The predictive modeling features of two general data mining systems, Microsoft SQL Server and IBM Intelligent Miner, are compared. The neural networks, decision tree, time series, and transform regression models are evaluated. It is shown that the data mining algorithms return quite accurate prediction results. The best results are achieved using the IBM's transform regression algorithm. [ABSTRACT FROM AUTHOR]

The development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm. The possibilities of improving the quality of regulation, which can be found in the literature, most often include various methods of coordination of the operation of the transformer regulator with various devices operating in the Medium-Voltage (MV) network. This coordination can be decentralized or centralized. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. The goal of the authors was to create an algorithm that extends the functionality of typical transformer control algorithms. The proposed solution allows for reducing the risk of voltage collapse. The performance of the proposed algorithm was validated using multivariate computer simulations and tests with the use of a physical model of the distribution network. The DIgSILENT PowerFactory environment was used to develop the simulation model of the proposed algorithm. Then, tests were conducted on real devices installed in the LINTEˆ2 Laboratory at the Gdańsk University of Technology, Poland. Selected test results are included in this paper. All results have shown that the proposed algorithm makes it possible to increase the reserve of the voltage stability of the node, in which it is applied, thus mitigating the risk of a voltage collapse occurring. The proposed algorithm does not require complex and costly technical solutions. Owing to its simplicity, it has a high potential for practical application, as confirmed by the real-time control experiment in the laboratory. [ABSTRACT FROM AUTHOR]

• A hybrid node to satisfy thermal comfort needs is analysed. • The heating & cooling node is assisted by solar and/or district heat. • Modular structure of the node allows for flexible reconfiguration of used devices. • The substation control can follow economical or environmental optimization procedure. • Potential of the control algorithm is assessed by the comparison with reference case. The development and implementation of 4th generation advanced heating and cooling nodes is needed in the face of growing, and more and more differential thermal comfort needs. The paper introduces a unique novel structure of hybrid heating and cooling node designed, constructed and already operated under moderate climate conditions of Poland. The substation integrates centralized district heat rate with locally produced useful heat gain from solar thermal collectors. The system driven both by heat and electricity delivers central heating, domestic hot water, cooling power, and low-temperature waste heat. This manuscript describes the simulation model, preliminary validation results, proposes a method for smart control of the node with a flexibly chosen optimization criterion and shows its impact. Creation of the control procedure satisfying economic or environmental savings objective functions is presented and discussed. The procedure was built upon assumed economic data and boundary conditions. Its potential is verified by means of simulation on validated component models. Depending on function-defined thermal comfort needs, current surrounding conditions and chosen optimization criterion, implementing the procedure may contribute to savings of variable scale if compared to a reference case. Preliminary simulation results revealed that in average, the by applying the economic optimization criterion, the cumulative operational costs become 1/3 of the reference case. At the same time, if the environmental optimization criterion is considered, the cumulative harmful substances emission indicator can be decreased less significantly: by 0.6%. [ABSTRACT FROM AUTHOR]