Baltic Europe, i.e. the sea and inland hinterland, form a unique macro-regional unit. Strong collaboration links as well as competition in the Baltic Sea Region are an inherent feature of the region from the beginnings of its civilization development. The article shows the forty-year-long Baltic integration process and the Polish scientific contribution to the process. Since 2004, the Baltic has become an internal EU sea. This fact no doubt strengthened cooperation of the countries around the Baltic Sea. In many spheres, these ties take the form of networking. An important stimulus for further integrations is the EU Strategy for the Baltic Sea Region. Political stabilisation and economic development may transform, in a longer time span, the emerging transnational Baltic Europe into a new economic and cultural European centre.
This paper estimates the magnitude of the Baumol-Bowen and Balassa-Samuleson effects in the Polish economy. The purpose of the analysis is to establish to what extent the differential price dynamics in Poland and in the euro area and the real appreciation of PLN against EUR are explained by the differential in respective productivity dynamics. The historical contribution of the Baumol-Bowen effect to Polish inflation rate is estimated at 0.9 − 1.0 percentage points in the short run. According to estimation results, the Balassa-Samuelson effect contributed around 0.9 to 1.0 percentage point per annum to the rate of relative price growth between Poland and the euro area and 1.0 to 1.2 p.p. to real exchange rate appreciation. The long-run effects are of an approximately twice larger magnitude. Sub-sample calculations and productivity trends over the last decade suggest that this impact should be declining. However, its size is still non-negligible for policymakers in the context of euro adoption in Poland.
The paper investigates the possibility of utilisation of heat-recirculating systems for fuel conversions having low net thermal effect. The experimental part is conducted with an electrically heated heat exchanger. It is shown that heat-recirculating systems can operate under superadiabatic conditions. Their thermal characteristics are provided by means of the dependencies of heat recirculation ratio on process parameters. Further, the heat-recirculating catalytic combustion system is characterised via combustion bifurcation diagrams. The similarities and differences of both those heat-recirculating systems are qualitatively compared and explained. Bifurcation characteristics proves to be useful tools in concise description of practical complex heat-recirculating fuel conversion systems in energy generation.
The paper presents local dynamic approach to integration of an ensemble of predictors. The classical fusing of many predictor results takes into account all units and takes the weighted average of the results of all units forming the ensemble. This paper proposes different approach. The prediction of time series for the next day is done here by only one member of an ensemble, which was the best in the learning stage for the input vector, closest to the input data actually applied. Thanks to such arrangement we avoid the situation in which the worst unit reduces the accuracy of the whole ensemble. This way we obtain an increased level of statistical forecasting accuracy, since each task is performed by the best suited predictor. Moreover, such arrangement of integration allows for using units of very different quality without decreasing the quality of final prediction. The numerical experiments performed for forecasting the next input, the average PM10 pollution and forecasting the 24-element vector of hourly load of the power system have confirmed the superiority of the presented approach. All quality measures of forecast have been significantly improved.
The objectives of this research are to study the direct influence on the competitive advantage
and pattern development of variables affecting the competitive advantage of the Thai oil
palm industry. This research employs a quantitative research method. The population for
the study consists of 150 oil palm industrial operators in Thailand. Questionnaires are used
in the data collection and the data are analyzed by using SEM. The research results reveal
that the Knowledge Management Process and Supply Chain Integration positively influence
the competitive advantage in the quality, delivery, and cost. The competitive advantage
receives a positive direct impact from the Knowledge Management Process and Supply
Chain Integration. The variation of competitive advantage can be explained as 84%. The
obtained results can be used for developing the industry to create economic growth and
sustainable competitive advantage.
Rescheduling is a frequently used reactive strategy in order to limit the effects of disruptions
on throughput times in multi-stage production processes. However, organizational deficits
often cause delays in the information on disruptions, so rescheduling cannot limit disruption
effects on throughput times optimally. Our approach strives for an investigation of
possible performance improvements in multi-stage production processes enabled by realtime
rescheduling in the event of disruptions. We developed a methodology whereby we
could measure these possible performance improvements. For this purpose, we created and
implemented a simulation model of a multi-stage production process. We defined system
parameters and varied factors according to our experiment design, such as information delay,
lot sizes and disruption durations. The simulation results were plotted and evaluated
using DoE methodology. Dependent on the factor settings, we were able to prove large improvements
by real-time rescheduling regarding the absorption of disruption effects in our
experiments.
Research focused on integration of machine operators with information flow in manufacturing process according to Industry 4.0 requirements are presented in this paper. A special IT system connecting together machine operators, machine control, process and machine monitoring with companywide IT systems is developed. It is an answer on manufacture of airplane industry requirements. The main aim of the system presented in the article is full automation of information flow between a management level represented by Integrated Management IT System and manufacturing process level. From the management level an information about particular orders are taken, back an on-line information about manufacturing process and manufactured parts are given. System allows automatic identification of tasks for machine operator and particular currently machined part. Operator can verify information about process and tasks. System allows on-line analyzing process data. It is based on information from machining acquired: machine operator, process and machine monitoring systems and measurement devices handled by operator. Process data is integrated with related order as a history of particular manufactured part. System allows for measurement data analysis based on Statistical Process Control algorithm dedicated for short batches. It supports operator in process control. Measurement data are integrated with order data as a part of history of manufactured product. Finally a conception of Cyber-Physical Systems applying in integrated Shop Floor Control and Monitoring systems is presented and discussed.
The dynamic development of wind power in recent years has generated the demand for production forecasting tools in wind farms. The data obtained from mathematical models is useful both for wind farm owners and distribution and transmission system operators. The predictions of production allow the wind farm operator to control the operation of the turbine in real time or plan future repairs and maintenance work in the long run. In turn, the results of the forecasting model allow the transmission system operator to plan the operation of the power system and to decide whether to reduce the load of conventional power plants or to start the reserve units.
The presented article is a review of the currently applied methods of wind power generation forecasting. Due to the nature of the input data, physical and statistical methods are distinguished. The physical approach is based on the use of data related to atmospheric conditions, terrain, and wind farm characteristics. It is usually based on numerical weather prediction models (NWP). In turn, the statistical approach uses historical data sets to determine the dependence of output variables on input parameters. However, the most favorable, from the point of view of the quality of the results, are models that use hybrid approaches. Determining the best model turns out to be a complicated task, because its usefulness depends on many factors. The applied model may be highly accurate under given conditions, but it may be completely unsuitable for another wind farm.
This study presents cause-effect dependencies between inputs and outputs of business transitions that are software objects designed for processing information-decision state variables in integrated enterprise process control (EntPC) systems. Business transitions are elementary components of controlling units in enterprise processes that have been defined as self-controlling, generalized business processes, which may serve not only as business processes but also as business systems or their roles. Business events, which have zero durations by definition, are interpreted as executions of business actions that are main operations of business transitions. Any ordered set of business actions, performed in the controlling unit of a given enterprise process and attributed to the same discrete-time instant, is referred to as ‘the information-decision process’. The i-d processes may be substituted by managerial business processes, performed on the lower organizational level, where durations of activity executions are greater than zero, but discrete-time periods are considerably shorter. In such a case, procedures of business actions are performed by corresponding activities of managerial processes, but on the level of business transitions the durations of their executions are imperceptible, and many different business events may occur at the same discrete-time instant. It has been demonstrated in the paper how to control business actions to ensure that a given i-d state variable may not change more than once at a given instant. Furthermore, the rules of designing the i-d process structures, which prevent random changes of transitory states, have been presented.
The aim of this paper is to analyze various CO2 compression processes for post-combustion CO2 capture applications for 900 MW pulverized coal-fired power plant. Different thermodynamically feasible CO2 compression systems will be identified and their energy consumption quantified. A detailed thermodynamic analysis examines methods used to minimize the power penalty to the producer through integrated, low-power compression concepts. The goal of the present research is to reduce this penalty through an analysis of different compression concepts, and a possibility of capturing the heat of compression and converting it to useful energy for use elsewhere in the plant.
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