The acoustic climate assessment needed for the selection of solutions (technical, legal and organisational), which will help to minimise the acoustic hazards in the analysed areas, is realised on the basis of acoustic maps. The reference computational algorithms, assigned to them, require very thorough preparation of input data for the considered noise source model representing - in the best possible way - the acoustic climate. These input data are burdened with certain uncertainties in this class of computational tasks. The uncertainties are related to the problem of selecting proper argument values (from the interval of their possible variability) for the modelled processes. This situation has a direct influence on the uncertainty of acoustic maps.

The idea of applying the interval arithmetic for the assessment of acoustic models uncertainty is formulated in this paper. The computational formalism assigned to the interval arithmetic was discussed. The rules of interval estimations for the model solutions determining the sound level distribution around the analysed noise source - caused by possible errors in the input data - were presented. The application of this formalism was illustrated in uncertainty assessments of modelling acoustic influences of the railway noise linear source on the environment.

The aim of this study was to establish reference values for 2D and M-mode measurements in Dachshunds. Basic echocardiographic data, including M-mode, 2D and spectral Doppler measurements, was collected, analyzed and compared between 41 healthy Dachshunds and 50 other healthy dogs of similar weight. Echocardiographic reference intervals were prepared for Dachshunds. Dachshunds had a smaller left ventricular diameter in diastole and systole and a thicker septum than other dog breeds. Male Dachshunds had larger diastolic and systolic left ventricular diameter than females. Reference intervals for 2D and M-mode measurements in healthy Dachshunds differ from other dogs of similar weight and should be used for this breed to assess chamber enlargement.

The fundamental problem from the point of view of pipeline exploitation in KGHM Polska Miedz S.A. is the very high overwearing of the pipes used for the transport of tailings, as well as determining the time of trouble-free operation of pipe system components. Failures involve significant financial outlays, severe restrictions on operation and in some cases even stopping operation. For this reason, it is vital to monitor the condition of the transport systems, as well as to determine the permissible service life of the pipe sections, after which segments at risk should be replaced or turned over in order to extend their further operation. This paper focuses on the application of interval numbers to assess the durability of piping systems. The calculations were made using classical interval numbers by using code written in INTLAB libraries. The correctness of the solutions obtained was verified using the Monte Carlo method, assuming a uniform distribution of random variables.

The paper concerns the problem of treatment of the systematic effect as a part of the coverage interval associated with the measurement result. In this case the known systematic effect is not corrected for but instead is treated as an uncertainty component. This effect is characterized by two components: systematic and random. The systematic component is estimated by the bias and the random component is estimated by the uncertainty associated with the bias. Taking into consideration these two components, a random variable can be created with zero expectation and standard deviation calculated by randomizing the systematic effect. The method of randomization of the systematic effect is based on a flatten-Gaussian distribution. The standard uncertainty, being the basic parameter of the systematic effect, may be calculated with a simple mathematical formula. The presented evaluation of uncertainty is more rational than those with the use of other methods. It is useful in practical metrological applications.

In the paper, the variation of the intensity of the geomagnetic field force is analysed in time and space. For the research, the data from measurements of the intensity of the geomagnetic field force at four airports (Kaunas, Klaip˙eda, Palanga andVilnius) and 6 geomagnetic field repeat stations aswell as the data from Belsk Magnetometric Observatory (Poland) were used. For the data analysis, the theory of covariance functions was applied. The estimates of the cross-covariance functions of the measured intensity of the geomagnetic field force or the estimates of auto-covariance functions of single data were calculated according to the random functions created from the force intensity measurement data arrays. The estimates of covariance functions were calculated upon varying the quantization interval on the time scale and applying the software created using Matlab package of procedures. The impact of radars of airports on the intensity of geomagnetic field variation and on changes of their covariance functions was established.

The In the paper, we investigate two single processor problems, which deal with the process of negotiation between a producer and a customer about delivery time of final products. This process is modelled by a due interval, which is a generalization of well known classical due date and describes a time interval, in which a job should be finished. In this paper we consider two diffierent mathematical models of due intervals. In both considered problems we should find such a schedule of jobs and such a determination of due intervals to each job, that the generalized cost function is minimized. The cost function is the maximum of the following three weighted parts: the maximum tardiness, the maximum earliness and the maximum due interval size. For the first problem we proved several properties of its optimal solution and next we show the mirror image property for both of considered problems, which helps us to provide an optimal solution for the second problem.

Reference intervals (RIs) are one of the essential elements in the procedure of disease diagnosis. This is especially true for feline species in which RI is less available than in canine species. RIs are affected by biological, geographical and instrumental factors, yet published RIs with incomplete background are popularly used. Inappropriate interpretations of RIs may affect classification of disease and subsequent treatment. In this study, we demonstrated the step-by-step establishment of feline RIs following the American Society for Veterinary Clinical Pathology (ASVCP) reference interval guideline. A total of 51 parameters were examined, including 20 hematology and 31 biochemistry parameters, and the results were compared to one local RI and two foreign RIs. Overall, about 29% (10/35) of tested parameters were different form local RIs and 60% (30/50) were different from the two foreign RIs, highlighting geographical variations. A higher upper reference limit (URL) in red blood cell count (RBC), hematocrit (Hct), Hemoglobin (Hgb), albumin, creatinine and lower URL in potassium and white blood cell count (WBC) were identified, which may impact the interpretation. In addition, statistical analysis of age and gender were factored separately and indicated that 10 parameters were significantly higher in the adult group. For the impact of gender, percentage of basophil and total iron-binding capacity (TIBC) were lower in female and male cats, respectively. In conclusion, we have demonstrated that it is desirable to establish in-house RIs or RIs of local sources. An age specific RI for the geriatric feline population is advisable for better diagnosis and monitoring the disease.

Civil engineering is one of the many fields of occurrences of uncertain parameters. The present paper in an attempt to present and describe the most common methods used for inclusions of uncertain parameters . These methods can be applied in the area of civil engineering as well as for a larger domain. Definitions and short explanations of methods based on probability, interval analysis, fuzzy sets, and convex sets are presented. Selected advantages, disadvantages, and the most common fields of implementation are indicated.

An example of a cantilever beam presented in this paper shows the main differences between the methods. Results of the performed analysis indicate that the use of convex sets allows us to obtain an accuracy of results similar to stochastic models. At the same time, the computational speed characteristic for interval methods is maintained.

Hull consistency is a known technique to improve the efficiency of iterative interval methods for solving nonlinear systems describing steady-states in various circuits. Presently, hull consistency is checked in a scalar manner, i.e. successively for each equation of the nonlinear system with respect to a single variable. In the present poster, a new more general approach to implementing hull consistency is suggested which consists in treating simultaneously several equations with respect to the same number of variables.

Progesterone (P4) is responsible for the main reproduction processes. Concentration of P4 varies widely among different determination methods, and interpretation of these values may be difficult. The objective of the current study was to assess the agreement of three different enzyme immunoassays (ELISA) in relation to radioimmunoassay (RIA) of P4 concentration assessment of beef cow serum samples. Samples were collected randomly considering high (pregnant cows) and low (non-pregnant cows) P4 concentrations. Depending on the P4 assessment method, four groups were created as follows: Group 1 – direct samples assessed by ELISA, Group 2 – extracted samples assessed by ELISA, Group 3 – samples assessed by automated ELISA, and Group 4 – samples assessed by RIA.

The mean progesterone concentration was 4.50 ng/mL, 1.24 ng/mL, 4.07 ng/mL and 4.39 ng/mL from Group 1 to Group 4, respectively. The mean difference (MD) between Group 1, Group 2 and Group 3 individually compared with Group 4 was −0.10 ± 1.24 ng/mL, 3.15 ± 3.58 ng/mL and 0.33 ± 1.42 ng/mL, and the 95% confidence interval (CI) for the differences (s) was from −0.99 to 0.78 ng/mL, from 0.59 to 5.71 ng/mL, and from −0.69 to 1.34 ng/mL, respectively. The confidence interval for the lower and upper limit of the agreement ranged from −4.12 to −1.05 ng/mL and from 0.84 to 3.91 ng/mL between Group 1 and Group 4, from −8.45 to 0.42 ng/ mL and from 5.88 to 14.75 ng/mL between Group 2 and Group 4, from −4.29 to −0.76 ng/mL, and from 1.41 to 4.94 ng/mL between Group 3 and Group 4.

Our findings show that the best agreement with RIA was observed for Group 1 and Group 3, while the agreement in the extraction method was least accurate.

According to metrological guidelines and specific legal requirements, every smart electronic electricity meter has to be constantly verified after pre-defined regular time intervals. The problem is that in most cases these pre-defined time intervals are based on some previous experience or empirical knowledge and rarely on scientifically sound data. Since the verification itself is a costly procedure it would be advantageous to put more effort into defining the required verification periods. Therefore, a fixed verification interval, recommended by various internal documents, standardised evaluation procedures and national legislation, could be technically and scientifically more justified and consequently more appropriate and trustworthy for the end user. This paper describes an experiment to determine the effect of alternating temperature and humidity and constant high current on a smart electronic electricity meter’s measurement accuracy. Based on an analysis of these effects it is proposed that the current fixed verification interval could be revised, taking into account also different climatic influence. The findings of this work could influence a new standardized procedure in respect of a meter’s verification interval.

Manufacturing errors (MEs) are unavoidable in product fabrication. The omnipresence of manufacturing errors (MEs) in product engineering necessitates the development of robust optimization methodologies. In this research, a novel approach based on the morphological operations and interval field (MOIF) theory is proposed to address MEs in the discrete-variable-based topology optimization procedures. On the basis of a methodology for deterministic topology optimization (TO) based on the Min-Cut, MOIF introduces morphological operations to generate geometrical variations, while the dimension of the structuring element is dynamically set by the interval field function’s output. The effectiveness of the proposed approach as a powerful tool for accounting for spatially uneven ME in the TOs has been demonstrated.

Rainfall is one of the main components of the hydrologic cycle; thus, the availability of accurate rainfall data is fundamental for designing and operating water resources systems and infrastructure. This study aims to develop an empirical model of rainfall intensity ( I_t,p) as a function of its probability ( p) and duration ( t). In 1999–2020, data on the hourly duration of rainfall were collected from automatic rainfall recorder (ARR) gauges. The empirical model has been developed using a statistical approach based on duration ( t) and probability ( p), and subsequently they have been validated with those obtained from ARR data. The resulting model demonstrates good performance compared with other empirical formulas (Sherman and Ishiguro) as indicated by the percent bias ( PBIAS) values (2.35–3.17), ratio of the RMSE (root mean square error) between simulated and observed values to the standard deviation of the observations ( RSR, 0.028–0.031), Nash–Sutcliffe efficiency ( NSE, 0.905–0.996), and index of agreement (d, 0.96–0.98) which classified in the rating of “very good” in model performance. The reliability of the estimated intensity based on the empirical model shows a tendency to decrease as duration ( t) increases, and a good accuracy mainly for the rainfall intensity for shorter periods (1-, 2-, and 3-hours), whereas low accuracy for long rainfall periods. The study found that the empirical model exhibits a reliable estimate for rainfall intensity with small recurrence intervals ( Tr) 2-, 5-, 10-, and a 20-year interval and for a shorter duration ( t). Validation results confirm that the rainfall intensity model shows good performance; thus, it could be used as a reliable instrument to estimate rainfall intensity in the study area.

A new method of Electrocardiogram (ECG) features extraction is proposed in this paper. The purpose of this study is to detect the main characteristics of the signal: P, Q, R, S, and T, then localize and extract its intervals and segments. To do so we first detect peaks, onsets and offsets of the signal's waveform by calculating the slope change (SC) coefficients and consequently, the peaks of the signal are determined. The SC coefficients are based on the calculation of the integral of two-scale signals with opposite signs. The simulation results of our algorithm applied on recordings of MIT-BIH arrhythmia electrocardiogram database show that the proposed method delineates the electrocardiogram waveforms and segments with high precision.

In this paper a new method of frequency jumps detection in data from atomic clock comparisons is proposed. The presented approach is based on histogram analysis for different time intervals averaging phasetime data recorded over a certain period of time. Our method allows identification of multiple frequency jumps for long data series as well to almost real-time jump detection in combination with advanced filtering. Several methods of preliminary data processing have been tested (simple averaging, moving average and Vondrak filtration), to achieve flexibility in adjusting the algorithm parameters for current needs which is the key to its use in determining ensemble time scale or to control systems of physical time scales, such as UTC(PL). The best results have been achieved with the Vondrak filter.

The Bulletin of the Polish Academy of Sciences: Technical Sciences (Bull.Pol. Ac.: Tech.) is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics.

Journal Metrics: JCR Impact Factor 2018: 1.361, 5 Year Impact Factor: 1.323, SCImago Journal Rank (SJR) 2017: 0.319, Source Normalized Impact per Paper (SNIP) 2017: 1.005, CiteScore 2017: 1.27, The Polish Ministry of Science and Higher Education 2017: 25 points.

Abbreviations/Acronym: Journal citation: Bull. Pol. Ac.: Tech., ISO: Bull. Pol. Acad. Sci.-Tech. Sci., JCR Abbrev: B POL ACAD SCI-TECH Acronym in the Editorial System: BPASTS.

A non-classical model of interval estimation based on the kernel density estimator is presented in this paper. This model has been compared with interval estimation algorithms of the classical (parametric) statistics assuming that the standard deviation of the population is either known or unknown. The non-classical model does not have to assume belonging of random sample to a normal distribution. A theoretical basis of the proposed model is presented as well as an example of calculation process which makes possible determining confidence intervals of the expected value of long-term noise indicators Aden and LN. The statistical analysis was carried out for 95% interval widths obtained by using each of these models. The inference of their usefulness was performed on the basis of results of non-parametric statistical tests at significance level α = 0.05. The data used to illustrate the proposed solutions and carry out the analysis were results of continuous monitoring of traffic noise recorded in 2004 in one of the main arteries of Krakow in Poland.

A novel approach for treating the uncertainty about the real levels of finished products during production planning and scheduling process

is presented in the paper. Interval arithmetic is used to describe uncertainty concerning the production that was planned to cover potential

defective products, but meets customer’s quality requirement and can be delivered as fully valuable products. Interval lot sizing and

scheduling model to solve this problem is proposed, then a dedicated version of genetic algorithm that is able to deal with interval

arithmetic is used to solve the test problems taken from a real-world example described in the literature. The achieved results are compared

with a standard approach in which no uncertainty about real production of valuable castings is considered. It has been shown that interval

arithmetic can be a valuable method for modeling uncertainty, and proposed approach can provide more accurate information to the

planners allowing them to take more tailored decisions.

The paper describes the construction, operation and test results of three most popular interpolators from a viewpoint of time-interval (TI) measurement systems consisting of many tapped-delay lines (TDLs) and registering pulses of a wide-range changeable intensity. The comparison criteria include the maximum intensity of registered time stamps (TSs), the dependency of interpolator characteristic on the registered TSs’ intensity, the need of using either two counters or a mutually-complementing pair counter-register for extending a measurement range, the need of calculating offsets between TDL inputs and the dependency of a resolution increase on the number of used TDL segments. This work also contains conclusions about a range of applications, usefulness and methods of employing each described TI interpolator. The presented experimental results bring new facts that can be used by the designers who implement precise time delays in the field-programmable gate arrays (FPGA).

A new time interval/frequency generator with a jitter below 5 ps is described. The time interval generation mechanism is based on a phase shifting method with the use of a precise DDS synthesizer. The output pulses are produced in a Spartan-6 FPGA device, manufactured by Xilinx in 45 nm CMOS technology. Thorough tests of the phase shifting in a selected synthesizer are performed. The time interval resolution as low as 0.3 ps is achieved. However, the final resolution is limited to 500 ps to maximize precision. The designed device can be used as a source of high precision reference time intervals or a highly stable square wave signal of frequency up to 50 MHz.

In this work, a fast 32-bit one-million-channel time interval spectrometer is proposed based on field programmable gate arrays (FPGAs). The time resolution is adjustable down to 3.33 ns (= T, the digitization/discretization period) based on a prototype system hardware. The system is capable to collect billions of time interval data arranged in one million timing channels. This huge number of channels makes it an ideal measuring tool for very short to very long time intervals of nuclear particle detection systems. The data are stored and updated in a built-in SRAM memory during the measuring process, and then transferred to the computer. Two time-to-digital converters (TDCs) working in parallel are implemented in the design to immune the system against loss of the first short time interval events (namely below 10 ns considering the tests performed on the prototype hardware platform of the system). Additionally, the theory of multiple count loss effect is investigated analytically. Using the Monte Carlo method, losses of counts up to 100 million events per second (Meps) are calculated and the effective system dead time is estimated by curve fitting of a non-extendable dead time model to the results (τNE = 2.26 ns). An important dead time effect on a measured random process is the distortion on the time spectrum; using the Monte Carlo method this effect is also studied. The uncertainty of the system is analysed experimentally. The standard deviation of the system is estimated as ± 36.6 × T (T = 3.33 ns) for a one-second time interval test signal (300 million T in the time interval).

Necessary and sufficient conditions for robust stability of the positive discrete-time interval system with time-delays are established.

It is shown that this system is robustly stable if and only if one well de?ned positive discrete-time system with time-delays is asymptotically stable. The considerations are illustrated by numerical example.

Simple new necessary and sufficient conditions for asymptotic stability of the positive linear discrete-time systems with delays in states are established. It is shown that asymptotic stability of the system is equivalent to asymptotic stability of the corresponding positive discrete-time system without delays of the same size. The considerations are illustrated by numerical examples.