Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 10
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

In spite of technological, logistic and economic difficulties, interest in renewable energy sources in the world is consistently increasing. This trend is also observed in Poland, mainly due to the urgent need to tackle the problem of climate change, which is caused by the increasing concentration of gaseous pollutants in the atmosphere. The paper presents a short script of the issue of estimating renewable energy resources in Poland in the context of creating local low carbon economy plans at the level of municipalities/counties where RES sources should be taken into account. The author proposed an individual approach to estimate the potential of RES, taking the local conditions and the short characteristics of the small and medium companies sector in Poland into account. These companies have a great application potential to increase the share of renewable energies and to improve energy efficiency in their business. The actions, which are taken by the Ministry of Energy in the field of civil energy development, enhancing local energy security and the sustainable development of renewable energy resources support the development of energy clusters covering one district or five municipalities. In the article, the author presents data on the number of companies possessing a concession for generating electricity in RES installations in the power range from 40 kW to 200 kW. These companies can largely be the nucleus for creating a local cluster in which microgrids will be a key element.

Go to article

Authors and Affiliations

Tomasz Mirowski
Download PDF Download RIS Download Bibtex

Abstract

The primary aim of this paper was to assess the development of prosumer energy sector in Poland. In the first point, the basic notions connected with prosumer energy (micro-installation, prosumer) were discussed on the basis of Law of Renewable Energy Sources of February 20, 2015 (Journal of Laws, item 478, as amended) and the main aspects of the European Union energy policy where presented in the context of the development of the prosumer energy sector. In this part of the study, numerous benefits for the Polish economy and consumers of electrical energy, connected with the expansion of prosumer energy sector, were presented. On the other hand, many obstacles which stall this sector in Poland were noticed. In the second point the most important regulations from the Law of Renewable Energy Sources of February 20, 2015 were analyzed (In the second point the most important regulations from the Law of Renewable Energy Sources of February 20, 2015 (hereinafter: the RES act) were analyzed). On the basis of this legal act, the so called “rebate system”, which is currently used in Poland to support prosumers of electrical energy, was described. Moreover, many legal and administrative simplifications implemented by the RES act were indicated. The analytical approach to the RES Act in this study resulted in the detection of many regulations in this legal act which may have an adverse impact on the development of the prosumer energy sector in Poland. In the third point, programs co-financed by the Polish government or the European Union, which financially support the purchase and installation of energy technologies using RES, were described. Statistical data connected with the prosumer energy sector in Poland was presented in the fourth point of this paper. On the basis thereof, the authors attempted to find the correlation between the number of prosumers and the share of the amount of electrical energy from renewable energy sources in gross electrical energy consumption. In the fifth point issues connected with energy technologies used in the Polish prosumer energy sector were discussed. Moreover, this point focuses on the great popularity of photovoltaic modules among Polish prosumers and results in the reluctance of Polish prosumers to install wind microturbines and small hydroelectric power plants.

Go to article

Authors and Affiliations

Jan Kuchmacz
Łukasz Mika
ORCID: ORCID
Download PDF Download RIS Download Bibtex

Abstract

The changes in the domestic solid fuel market (including forecasted increases in the fuel prices) and the growing requirements related to actual environmental standards, result in increased interest in renewable energy sources, such as biomass, wind and solar energy. These sources will allow to achieve reduction in the CO2 emission, and consequently – avoid environmental costs after 2020. Therefore, the development of distributed energy systems, based on the use of biomass boilers, gas boilers and high efficiency combined heat and power units, will enable the fulfillment of current standards in the field of energy efficiency and emission of pollutants to the atmosphere. It should be emphasized that the actions taken to reduce emissions (e.g. anti-smog act) will contribute to reducing coal consumption in the municipal and housing sector (households, agriculture and other customers) in favor of biomass and other renewable energy sources. The article reviews selected biomass technologies:

- fluidized, dust and grate boilers,

- straw-fired boilers,

- cogeneration systems powered by biomass,

- torrefaction and biomass carbonisation.

The mentioned technologies are characterized by a high potential of in the field of dynamic development and practical application in the coming years. Thus, they can improve difficult situation in the distributed energy sector with a capacity up to 50 MW.

Go to article

Authors and Affiliations

Tomasz Mirowski
Eugeniusz Mokrzycki
Mariusz Filipowicz
Krzysztof Sornek
Download PDF Download RIS Download Bibtex

Abstract

In this article, the contribution of renewable energy sources (RES) to the worldwide electricity production was analyzed. The scale of development and the importance of RES in the global economy as well as the issues and challenges related to variability of these sources were studied. In addition, the chemical conversion of excess energy to renewable methanol has been presented. The European Union regulations and targets for the years 2020 and 2030 concerning greenhouse gases reduction were taken into consideration. These EU restrictions exact the further development of renewable energy sources, in particular, the improvement of their efficiency which is closely related to economics. Moreover, as a part of this work, energy storage were described as one of the ways to increase the competitiveness of renewable energy sources with respect to conventional energy. A method for the conversion of carbon dioxide separated from high-carbon industries with hydrogen obtained by the over-production of green energy were described. The use of methanol in the chemical industry and global market have been reviewed and thus an increasing demand was observed. Additionally, the application of renewable methanol as fuels, in pure form and after a conversion of methanol to dimethyl ether and fatty acid methyl esters has been discussed. Hence, the necessity of modifying car engines in order to use pure methanol and its combination with petrol also was analyzed.

Go to article

Authors and Affiliations

Szymon Dobras
Lucyna Więcław-Solny
Tadeusz Chwoła
Aleksander Krótki
Andrzej Wilk
Adam Tatarczuk
Download PDF Download RIS Download Bibtex

Abstract

This paper presents the main dilemma of development of the Polish energy sector on the 20th anniversary of the first liberalization directive of the European Union, which created the energy market. The situation in the Polish energy sector based on fossil fuels, its transformation into lower emission one is closely connected to the process of restructuring and further development of the mining sector. On the other hand, we are witnessing the development of RES, household installations producing electricity with storage and the electrification of public transport. The investments in new, large scale fossil fuel fired power plants are very expensive and not economically proven when electricity prices are low. Until the new direction of investment in energy sector will be decided, the option of the lasting of the operating existing power units seems to be a good proposal. Is the thesis: “The energy security of Poland should be fully based on indigenous sources, generation and distribution assets, delivering electricity to end users. Ensuring competitive energy prices to the economy and households, the market should be fully open to producers and consumers, including chip electricity arising from the European single market” the right assumption for the Polish energy policy?

Go to article

Authors and Affiliations

Stanisław Tokarski
Download PDF Download RIS Download Bibtex

Abstract

This research analyzes factors affecting the scientific success of
central bankers. We combine data from the RePEc and EDIRC databases,
which contain information about economic publications of authors from
182 central banks. We construct a dataset containing information about
3312 authors and almost 80,000 scientific papers published between 1965
and 2020. The results from Poisson regressions of citation impact
measure (called the h-index) on a number of research features
suggest that economists from the U.S. Federal Reserve Banks,
international financial institutions, and some eurozone central banks
are cited more frequently than economists with similar characteristics
from central banks located in emerging markets. Researchers from some
big emerging economies like Russia or Indonesia are cited particularly
infrequently by the scientific community. Beyond these outcomes, we
identify a significant positive relationship between research networking
and publication success. Moreover, economists cooperating with highly
cited scientists also obtain a high number of citations even after
controlling for the size of their research networks.
Go to article

Authors and Affiliations

Jakub Rybacki
1
Dobromił Serwa
2

  1. Polish Economic Institute, Poland
  2. SGH Warsaw School of Economics, Collegium of Economic Analysis, Warsaw, Poland
Download PDF Download RIS Download Bibtex

Abstract

The paper is focused on use of renewable energy sources for energy production with special attention paid to the biomass wastes. Type and potential of wastes biomass, which can be used for production of electric and thermal energy, were generally characterized, use of the biomass as energy source in Poland was discussed, existing reserves were estimated and basic strategic-and-legal acts, which refer to the considered problem were presented. A type of possible activities to increase the amount of alternative energy produced in Poland, in the light of requirement to achieve a determined ecological-and-energy target resulting from international agreements and EU legislation, were indicated.
Go to article

Authors and Affiliations

Danuta Domańska
Tomasz Zacharz
Download PDF Download RIS Download Bibtex

Abstract

Multi-focus image fusion is a method of increasing the image quality and preventing image redundancy. It is utilized in many fields such as medical diagnostic, surveillance, and remote sensing. There are various algorithms available nowadays. However, a common problem is still there, i.e. the method is not sufficient to handle the ghost effect and unpredicted noises. Computational intelligence has developed quickly over recent decades, followed by the rapid development of multi-focus image fusion. The proposed method is multi-focus image fusion based on an automatic encoder-decoder algorithm. It uses deeplabV3+ architecture. During the training process, it uses a multi-focus dataset and ground truth. Then, the model of the network is constructed through the training process. This model was adopted in the testing process of sets to predict the focus map. The testing process is semantic focus processing. Lastly, the fusion process involves a focus map and multi-focus images to configure the fused image. The results show that the fused images do not contain any ghost effects or any unpredicted tiny objects. The assessment metric of the proposed method uses two aspects. The first is the accuracy of predicting a focus map, the second is an objective assessment of the fused image such as mutual information, SSIM, and PSNR indexes. They show a high score of precision and recall. In addition, the indexes of SSIM, PSNR, and mutual information are high. The proposed method also has more stable performance compared with other methods. Finally, the Resnet50 model algorithm in multi-focus image fusion can handle the ghost effect problem well.
Go to article

Authors and Affiliations

K. Hawari
1
Ismail Ismail
1 2

  1. Universiti Malaysia Pahang, Faculty of Electrical and Electronics Engineering, 26300 Kuantan, Malaysia
  2. Politeknik Negeri Padang, Electrical Engineering Department, 25162, Padang, Indonesia
Download PDF Download RIS Download Bibtex

Abstract

The authors of this article were guided by the desire to show the profitability of using renewable energy sources and to facilitate decisions for future investors as to their choice. The article classifies energy sources and methods for converting renewable energy sources (RES) and presents a technical comparison of two electricity supply systems: a photovoltaic system and a household wind farm for a selected building. A residential, single-family building, inhabited by a family of three, was adopted for analysis. Photovoltaics, the use of solar radiation energy to produce electricity, is classified next to wind farms as the most dynamically developing renewable energy technology. When analysing in terms of technology renewable conversion methods that provide us with electricity, the better installation is the photovoltaic installation. By analysing the cost of renewable energy conversion technologies that provide us with electricity, the photovoltaic system becomes more beneficial, because with a similar investment price we get a much shorter payback period than in the case of a backyard wind power station.
Go to article

Authors and Affiliations

Wojciech Drozd
1
ORCID: ORCID
Marcin Kowalik
1
ORCID: ORCID

  1. Department of Construction Management, Tadeusz Kościuszko Cracow University of Technology, Warszawska 24 St., 31-155 Kraków, Poland
Download PDF Download RIS Download Bibtex

Abstract

The paper is focused on automatic segmentation task of bone structures out of CT data series of pelvic region. The authors trained and compared four different models of deep neural networks (FCN, PSPNet, U-net and Segnet) to perform the segmentation task of three following classes: background, patient outline and bones. The mean and class-wise Intersection over Union (IoU), Dice coefficient and pixel accuracy measures were evaluated for each network outcome. In the initial phase all of the networks were trained for 10 epochs. The most exact segmentation results were obtained with the use of U-net model, with mean IoU value equal to 93.2%. The results where further outperformed with the U-net model modification with ResNet50 model used as the encoder, trained by 30 epochs, which obtained following result: mIoU measure – 96.92%, “bone” class IoU – 92.87%, mDice coefficient – 98.41%, mDice coefficient for “bone” – 96.31%, mAccuracy – 99.85% and Accuracy for “bone” class – 99.92%.
Go to article

Bibliography

  1.  E. Stindel, et al., “Bone morphing: 3D morphological data for total knee arthroplasty” Comput. Aided Surg. 7(3), 156–168 (2002), doi: 10.1002/igs.10042.
  2.  F. Azimifar, K. Hassani, A.H. Saveh, and F.T. Ghomsheh, “A medium invasiveness multi-level patient’s specific template for pedicle screw placement in the scoliosis surgery”, Biomed. Eng. Online 16, 130 (2017), doi: 10.1186/s12938-017-0421-0.
  3.  L. Yahia-Cherif, B. Gilles, T. Molet, and N. Magnenat-Thalmann, “Motion capture and visualization of the hip joint with dynamic MRI and optical systems”, Comp. Anim. Virtual Worlds 15, 377–385 (2004).
  4.  V. Pekar, T.R. McNutt, and M.R. Kaus, “Automated modelbased organ delineation for radiotherapy planning in prostatic region”, Int. J. Radiat. Oncol. Biol. Phys. 60(3), 973–980 (2004).
  5.  D. Ravì, et al., “Deep learning for health informatics,” IEEE J. Biomed. Health. Inf. 21(1), 4–21 (2017), doi: 10.1109/JBHI.2016.2636665.
  6.  G. Litjens, et al., “A survey on deep learning in medical image analysis”, Med. Image Anal. 42, 60–88 (2017), doi: 10.1016/j. media.2017.07.005.
  7.  Z. Krawczyk and J. Starzyński, “YOLO and morphingbased method for 3D individualised bone model creation”, 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom (2020), doi: 10.1109/IJCNN48605.2020.9206783.
  8.  J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, 3431–3440 (2015), doi: 10.1109/CVPR.2015.7298965.
  9.  H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia, “Pyramid Scene Parsing Network,” 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, 6230–6239 (2017), doi: 10.1109/CVPR.2017.660.
  10.  O. Ronneberger, P. Fischer, and T. Brox, “U-Net: convolutional networks for biomedical image segmentation”, in Navab N., Hornegger J., Wells W., Frangi A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science, vol. 9351, Springer, Cham. (2015), doi: 10.1007/978-3-319-24574-4_28.
  11.  V. Badrinarayanan, A. Kendall, and R. Cipolla, “SegNet: A deep convolutional encoder-decoder architecture for image segmentation”, IEEE Trans. Pattern Anal. Mach. Intell. 39(12), 2481–2495 (2017), doi: 10.1109/TPAMI.2016.2644615.
  12.  Z. Krawczyk and J. Starzyński, “Deep learning approach for bone model creation”, 2020 IEEE 21st International Conference on Computational Problems of Electrical Engineering (CPEE), (2020), doi: 10.1109/CPEE50798.2020.9238678.
  13.  W. Qin, J. Wu, F. Han, Y. Yuan, W. Zhao, B. Ibragimov, J. Gu, and L. Xing, “Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation”, Phys. Med. Biol. 63(9), 95017 (2018), doi: 10.1088/1361‒6560/aabd19.
  14.  S. Nikolov, et al., “Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy”, Technical Report, ArXiv, (2018), doi: arXiv:1809.04430.
  15.  T.L. Kline, et al., “Performance of an artificial multi-observer deep neural network for fully automated segmentation of polycystic kidneys”, J Digit Imaging 30, 442–448 (2017), doi: 10.1007/s10278-017-9978-1.
  16.  A. Wadhwa, A. Bhardwaj, and V.S. Verma, “A review on brain tumor segmentation of MRI images”, Magn. Reson. Imaging 61, 247–259 (2019), doi: 10.1016/j.mri.2019.05.043.
  17.  J. Xu, X. Luo, G. Wang, H. Gilmore, and A. Madabhushi, “A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images”, Neurocomputing 191, 214–223 (2016), doi: 10.1016/j.neucom.2016.01.034.
  18.  Z. Swiderska-Chadaj, T. Markiewicz, J. Gallego, G. Bueno, B. Grala, and M. Lorent, “Deep learning for damaged tissue detection and segmentationin Ki-67 brain tumor specimens based on the U-net model”, Bull. Pol. Acad. Sci. Tech. Sci. 66(6), 849–856 (2018), doi: 10.24425/bpas.2018.125932.
  19.  S. Lindgren Belal, et. al., “Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CTbased 3D quantification of skeletal metastases”, Eur. J. Radiol. 113, 89–95 (2019), doi: 10.1016/j.ejrad.2019.01.028.
  20.  A. Klein, J. Warszawski, J. Hillengaß, and K.H. Maier-Hein, “Automatic bone segmentation in whole-body CT images”, Int J Comput Assist Radiol Surg. 14(1), 21–29 (2019), doi: 10.1007/s11548-018-1883-7.
  21.  J. Minnema, M. van Eijnatten, W. Kouw, F. Diblen, A. Mendrik, and J. Wolff, “CT image segmentation of bone for medical additive manufacturing using a convolutional neural network”, Comput. Biol. Med. 103, 130–139 (2018), https://doi.org/10.1016/j. compbiomed.2018.10.012.
  22.  T. Les, T. Markiewicz, T. Osowski, and M. Jesiotr, “Automatic reconstruction of overlapped cells in breast cancer FISH images”, Expert Syst. Appl. 137, 335–342 (2019).
  23.  F. Yokota, T. Okada, M. Takao, N. Sugano, Y. Tada, and Y. Sato, “Automated segmentation of the femur and pelvis from 3D CT data of diseased hip using hierarchical statistical shape model of joint structure”, Med Image Comput Comput Assist Interv., 811–818 (2019), doi: 10.1007/978-3-642-04271-3_98.
  24.  D. Gupta, “Semantic segmentation library”, accessed 19-Jan-202, [Online], Available: https: //divamgupta.com/image- segmentation/2019/06/06/ deep-learning-semantic-segmentation-keras.html.
  25.  A.B. Jung, et al., “Imgaug library”, accessed 01-Feb-2020, [Online], Available: https://github.com/aleju/imgaug (2020).
  26.  F. Chollet, et al., “Keras”, [Online], Available: https://keras.io, (2015).
  27.  M. Abadi, et al., “TensorFlow: Large-scale machine learning on heterogeneous systems”, [Online], Available: tensorflow.org, (2015).
  28.  K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition”, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, 770–778 (2016), doi: 10.1109/CVPR.2016.90.
  29.  K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition”, CoRR, (2015).
  30.  O. Russakovsky, et al., “ImageNet large scale visual recognition challenge”, Int. J. Comput. Vision 115(3), 211–252 (2015), doi: 10.1007/ s11263-015-0816-y.
  31.  VGG network weights, [Online], Available: https://www.robots.ox.ac.uk/~vgg/research/very_deep/
  32.  Resnet network weights, [Online], Available: https://github.com/KaimingHe/deep-residual-networks.
  33.  P. Leydon, M. O’Connell, D. Greene, K. M. Curran, “Bone Segmentation in Contrast Enhanced Whole-Body Computed Tomography”, arXiv (2020), https://arxiv.org/abs/2008.05223.
Go to article

Authors and Affiliations

Zuzanna Krawczyk
1
Jacek Starzyński
1

  1. Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland

This page uses 'cookies'. Learn more