Mathematical model of integrated thermal apparatus

Mathematical model for the integrated thermal apparatus was developed. It consists of program modules from which individualfurnace model can be generated. For the model generation elementary balance method was used. Generation of the individual modelincludes model formulation and parameters determination. Model formulation is based on first principles, heuristics and empirical results.Parameters determination is generally based on priory information, but it has to take into account specific conditions. The developed modelwas adapted for real time applications. For quantitative application developed model has to be calibrated. For the calibration theoperational furnace can be used. For model calibration of not existing furnace the priory knowledge and physical model can be used.Presented model was calibrated on experimental furnace. The results were gained by simulations

The Influence of Sex and Hybrid on the Fattening Parameters of Pigs

In the experiment, we investigated the effect of the hybrid combination and sex on the fattening parameters of pigs fed with the same feed. The analyzed group consisted of 27 animals. We used the final hybrids of BU x L x PIC and BU x PIC for the testing purposes. Feeding pigs with the mixture was the same for all the tested pigs. We evaluated the average daily gain (ADG) in grams (g), feed consumption ratio (FCR) in kilograms (kg), number of feeding days (FD) in two growth phases: Phase 1 - piglets (from weaning to 25 kg), Phase 2 - test (30-100 kg). The pigs of the hybrid combination LW x L x PIC (ADG – 533.6 g, p<0.01) had a higher intensity of growth after weaning, but the PIC x LW hybrid combination achieved a better efficiency of feed utilization (FCR – 1.56 kg, p<0.05). The sex differences were not statistically significant. During the growth period from 30 to 100 kg, better fattening parameters were reached by the hybrid LW x PIC (bigger ADG - 975.8 g, a smaller number of FD - 72.3, p<0.01). The differences regarding the FCR factor between the hybrids were not statistically significant. Better fattening parameters from 30 to 100 kilograms were achieved by barrows (ADG - 929.6 g, p<0.05; FD - 76.9, p<0.01; FCR - 2.69 kg, insignificant) in comparison to gilts. This work has been created with the support of KEGA 006SPU-4/2014 and VEGA 1/0818/16.Keywords: crossbreed, growth, sex, pig

Influence of the breeding environment factors on the number of the weaned piglets

Article Details: Received: 2020-10-22 | Accepted: 2020-11-27 | Available online: 2021-01-31https://doi.org/10.15414/afz.2021.24.mi-prap.131-134A prerequisite for the successful pig breeding isthe achievement of high reproductive performance, which can be influenced by several environmental factors. Therefore, the aim of our research was to assess the impact of the season, microclimatic indicators and technology of housing of the lactating sows on the number of  the weaned piglets in the litter. The experiment was performed on a production farm in Slovakia and a total of 800 litters were evaluated. The results have shown that the season had a statistically significant effect on the number of the weaned piglets (p<0.01),  least in the summer and  most of them in the fall. The highest number of the weaned piglets was found at the temperatures from 18 to 22 °C (p<0.05), temperatures outside the stated range had a negative impact on the number of the weaned piglets. An increase of the relative humidity - above 70% (p<0.05) and an increase in the flow - above 0,4 m.s-1 (p<0.05) led to a decrease in the number of the weaned piglets. In the housing with a freemovement of the lactating sows, the number of the weaned piglets was higher than with the restricted movement (p<0.05).Keywords: microclimate, technology, weaned pigletsReferencesBoudný, J. & Špička, J. (2012). The effect of production efficiency on economic results in pig breeding. Res. Pig Breeding, 6(1), 1-8.Close, W. (1992). Thermoregulation in piglets: Environmental and metabolic consequences. BSAP Occasional Publication,15, 25-33. https://doi.org/10.1017/S0263967X00004067English, P. R. & Edwards, S. A. (1996). Management of the nursing sow and her litter. In Dunkin A. C. & Taverner, M. (eds.). Pig Production. World Animal Science (Vol. C10). Amsterdam, Netherlands: Elsevier (pp. 113-140).Holmes, C. W. & Mount, L. E. (1967). Heat loss from groups of growing pigs under various conditions of environmental temperature and air movement. J. Anim. Prod., 9, 435-452. https://doi.org/10.1017/S0003356100042008Horký, P. (2014). Influence of increased dietary selenium on glutathione peroxidase activity and glutathione concentration in erythrocytes of lactating sows. Ann. Anim. Scie., 14(4), 869-882. https://doi.org/10.2478/aoas-2014-0056Matoušek, V. et al. (2013). Livestock breeding II. České Budějovice : JU ZF. In Czech.Myer, R. & Bucklin, R. (2018). Influence of hot-humid environment on growth performance and reproduction of swine. AN107: UF/IFAS Extension, 1-6.Nevrkla, P. et al. (2016). analysis of reproductive parameters in sows with regard to their health status. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 64, 481-486.https://doi.org/10.11118/actaun201664020481.Novák, P. & Rožňovský, J. (2009). Influence of microclimate on the pig performance. In Current knowledge about the pig breeding: proceedings from the International Scientific Conference 41 held on the occasion of the 90th anniversary of MZLU in Brno. Brno: MZLU (pp. 45-48). In Czech.Prunier, A. et al. (1996). Environmental and seasonal influences on the return-to-oestrus after weaning in primiparous sows. Livestock Production Science, 45, 103-110. https://doi.org/10.1016/0301-6226(96)00007-3Rodrígues, S. V., Plà, L. M. & Albornoz, V. M. (2012). Modeling tactical planning decisions through a linear optimization model in sow farms. Livest. Sci., 143(2-3), 162-171.Rolinec, M. (2020). The Effect of coconut oil addition to feed of pigs on rectal microbial diversity and bacterial abundance. Animals (Basel), 10(10), E1764. https://doi.org/10.3390/ani10101764Rozkot, M. (2014). Pigs technology and the public. Náš chov, 74(10), 63-66. In Czech.Sällvik, K. & Walberg, K. (1984). The effects of air velocity and temperature on the behaviour and growth of pigs. J. of Agricultural Engineering. Research, 30, 305-312. https://doi.org/10.1016/S0021-8634(84)80031-1Silva, B. A. N. et al. (2006). Effect of floor cooling on performance of lactating sows during summer. Livest. Sci., 105, 176-184. https://doi.org/10.1016/j.livsci.2006.06.007Suriyasomboon, A. et al. (2006). Effect of temperature and humidity on reproductive performance of crossbred sows in Thailand. Theriogenology, 65, 606-628. https://doi.org/10.1016/j.theriogenology.2005.06.005Vanerhaeghe, C. et al. (2010). Longitudinal field study to assess sow level risk factors associated with stillborn piglets. Anim. Reprod. Sci., 120(1-4), 78-83. https://doi.org/10.1016/j.anireprosci.2010.02.010Wegner, K. et al. (2014). Climatic effects on sow fertility and piglet survival under influence of a moderate climate. Animal,  8(9), 1526-1533. https://doi.org/10.1017/S1751731114001219

Analog-to-Information Conversion with Random Interval Integration

A novel method of analog-to-information conversion—the random interval integration—is proposed and studied in this paper. This method is intended primarily for compressed sensing of aperiodic or quasiperiodic signals acquired by commonly used sensors such as ECG, environmental, and other sensors, the output of which can be modeled by multi-harmonic signals. The main idea of the method is based on input signal integration by a randomly resettable integrator before the AD conversion. The integrator’s reset is controlled by a random sequence generator. The signal reconstruction employs a commonly used algorithm based on the minimalization of a distance norm between the original measurement vector and vector calculated from the reconstructed signal. The signal reconstruction is performed by solving an overdetermined problem, which is considered a state-of-the-art approach. The notable advantage of random interval integration is simple hardware implementation with commonly used components. The performance of the proposed method was evaluated using ECG signals from the MIT-BIH database, multi-sine, and own database of environmental test signals. The proposed method performance is compared to commonly used analog-to-information conversion methods: random sampling, random demodulation, and random modulation pre-integration. A comparison of the mentioned methods is performed by simulation in LabVIEW software. The achieved results suggest that the random interval integration outperforms other single-channel architectures. In certain situations, it can reach the performance of a much-more complex, but commonly used random modulation pre-integrator

Monitoring of Bridge Dynamics by Radar Interferometry

The paper presents the possibilities of radar interferometry in dynamic deformationmonitoring of bridge structures. The technology is increasingly used for this purposethanks to high accuracy of realized measurements and possibility to measure deformationat multiple places of the monitored structure. High frequency of realized measurements (upto 200 Hz) enables to determine the most of significant vibration modes of bridgedeformation. This technology is presented on real case study of the cycle bridge over theriver Morava near to Bratislava (Slovak republic). A spectral analysis of vibrationfrequencies is performed by discrete Fourier transformation. The evaluation of correctnessof the obtained deformation is performed by comparison of the results with accelerometerand total station measurements and FEM (Finite Element Method) model of the structure

Praćenje dinamičkih deformacija tehnoloških struktura

Building structures are extremely sensitive to the influence of outdoor conditions, especially the influence of wind, temperature changes in the surroundings caused by sunshine, and the effect of the building’s own or operating load. According to the resonance of the structure with the surroundings, vibrations and oscillations in relatively high frequency intervals (1–100.0 Hz) occur. These phenomena significantly affect the static and dynamic characteristics of structures as well as their safety and functionality. The paper provides an example of monitoring these phenomena using surveying methods and instrumentation. The monitored structure (a desorbing tower) has a cylindrical shape. The measurements were made by a total station with a measurement frequency ca 2 Hz. The main point of the paper is an analysis of the dynamic behaviour of the structure using different methods for the spectral analysis of a time series. The use of a fast Fourier Transform and a Lomb-Scargle periodogram is described, and the frequencies of the structure’s oscillation are calculated.Strukture zgrada iznimno su osjetljive na utjecaj vanjskih uvjeta, posebno na utjecaje vjetra, temperaturne promjene u okolini uzrokovane sunčevim zračenjem, a također i na utjecaj vlastitog ili operativnog opterećenja. Prema rezonanciji strukture s okolinom, javljaju se vibracije i oscilacije u relativno visokim frekvencijskim intervalima (1–100,0 Hz). Ta pojava znatno utječe na statičke i dinamičke karakteristike struktura, kao i na njihovu sigurnost i funkcionalnost. U radu se daje primjer praćenja tih pojava geodetskim metodama i instrumentima. Struktura koja se prati (desorpcijski toranj) ima cilindrični oblik. Mjerenja su provedena pomoću totalne stanice mjernom frekvencijom oko 2 Hz. Doprinos u radu je analiza dinamičkog ponašanja strukture upotrebom različitih metoda i spektralnih analiza vremenskog niza podataka. Opisana je upotreba brze Fourierove transformacije i Lomb-Scarglovog periodograma i izračunate frekvencije strukturnih oscilacija

Automatizovaný merací systém na kontinuálny monitoring mostov =Automated Measurement System for Continuous Bridge Monitoring

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Optimization Paradigm in the Signal Recovery after Compressive Sensing

Compressive sensing is a processing approach aiming to reduce the data stream from the observed object with the inherent sparsity using the optimal signal models. The compression of the sparse input signal in time or in the transform domain is performed in the transmitter by the Analog to Information Converter (AIC). The recovery of the compressed signal using optimization based on the differential evolution algorithm is presented in the article as an alternative to the faster pseudoinverse algorithm. Pseudoinverse algorithm results in an unambiguous solution associated with lower compression efficiency. The selection of the mathematically appropriate signal model affects significantly the compression efficiency. On the other hand, the signal model influences the complexity of the algorithm in the receiving block. The suitability of both recovery methods is studied on examples of the signal compression from the passive infrared (PIR) motion sensors or the ECG bioelectric signals