{"id":13,"date":"2018-05-10T12:10:16","date_gmt":"2018-05-10T10:10:16","guid":{"rendered":"http:\/\/drizzt.home.amu.edu.pl\/?page_id=13"},"modified":"2026-05-19T00:36:24","modified_gmt":"2026-05-18T22:36:24","slug":"publikacje","status":"publish","type":"page","link":"http:\/\/drizzt.home.amu.edu.pl\/?page_id=13","title":{"rendered":"Publikacje"},"content":{"rendered":"\n<\/a>\n\n\n\n

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A. Monografie<\/strong><\/p>\n\n\n\n

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  1. M. Krzy\u015bko, W. Wo\u0142y\u0144ski, T. G\u00f3recki<\/strong>, M. Skorzybut (2008). Systemy ucz\u0105ce si\u0119 – rozpoznawanie wzorc\u00f3w, analiza skupie\u0144 i redukcja wymiarowo\u015bci. WNT, Warszawa.<\/a><\/li>\n\n\n\n
  2. T. G\u00f3recki <\/strong>(2011). Podstawy statystyki z przyk\u0142adami w R. BTC, Legionowo<\/a>.<\/li>\n\n\n\n
  3. E. \u0141a\u017aniewska, T. G\u00f3recki<\/strong>, R. Chmielewski (2011). Konwergencja regionalna. Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu.<\/a><\/li>\n\n\n\n
  4. E. \u0141a\u017aniewska, J. Kurowska-Pysz, T. G\u00f3recki<\/strong>, K. Prytula, K. Plac (2024). War Refugees and the Labour Market. Taylor & Francis Group\/Routledge, Londyn.<\/a><\/li>\n<\/ol>\n\n\n\n
    \n\n\n\n

    B. Prace naukowe<\/strong><\/p>\n\n\n\n

      \n
    1. \u0141a\u017aniewska, E., G\u00f3recki, T.<\/strong>, Siemiatowski, F. (2026). The Polish-Ukrainian borderland through the prism of convergence and resilience from 2004 to 2020.<\/a> Bulletin of Geography. Socio-economic Series 72(72):51-63. (2024: IF: – 0.8)<\/strong><\/span><\/li>\n\n\n\n
    2. G\u00f3recki, T.<\/strong> (2026). From Expected Goals to Scoring at Least Once: An Event-Specific Summary of Aggregated Bernoulli Risk.<\/a> Entropy 28(5):527. (2024: IF: – 2.0)<\/strong><\/span><\/li>\n\n\n\n
    3. Jamroziak, K., Dytfeld, D., Kubicki, T., Dutka, M., Wr\u00f3bel, T., Giannopoulos, K., Ko\u0144ska, A., Druzd-Sitek, A., Tyczy\u0144ska, A., Olszewska-Szopa, M., Morawska, M., Szeremet, A., Kopi\u0144ska, A., Wi\u015bniewski, K., Czy\u017c, J., Helbig, G., Gil, L., Zaucha, J. M., Kruk-Kwapisz, D., Walewski, J., G\u00f3recki, T.<\/strong>, Pu\u0142a, B. (2026). Daratumumab or active observation for asymptomatic biochemical relapse in patients with multiple myeloma.<\/a> British Journal of Haematology 208(4):1314-1323. (2024: IF: – 3.8)<\/strong><\/span><\/li>\n\n\n\n
    4. Krzy\u017caniak, S., Cyplik, P., Bartkowiak, M., G\u00f3recki, T.<\/strong>, Koralewski, A. (2026). Simulation Studies on the Impact of Using Demand Forecasts Based on Deep Neural Networks for Inventory Replenishment Efficiency<\/a>. LogForum 22(1):111-124. (2024: IF: – 1.0)<\/strong><\/span><\/li>\n\n\n\n
    5. Skalski, M., Kowal-Wi\u015bniewska, E., Jaskiewicz-Rajewicz, K., Kiwerska, K., Bartochowska, A., Ustaszewski, A., G\u00f3recki, T., Majchrzak-Celi\u0144ska, A., Wierzbicka, M., Jarmu\u017c-Szymczak, M., Paluszczak, J. (2026). The methylation of LHX2, RAPGEFL1, RARB and RYR2 has prognostic significance in head and neck squamous cell carcinoma patients.<\/a> Journal of Applied Genetics. (2024: IF: – 1.9)<\/strong><\/span><\/li>\n\n\n\n
    6. G\u00f3recki, T.<\/strong>, Grzelak, B., Dyczkowski, K. (2026). Player position classification with fuzzy clustering. In: Mei, Y., Qian, C., Bai, Q., Xue, B., Khanna, S. (Eds), PRICAI 2025. Lecture Notes in Computer Science 16452. Springer, Singapore. 34-642. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    7. G\u00f3recki, T.<\/strong>, Grzelak, B., Dyczkowski, K. (2026). Predicting football outcomes and quantifying team strengths with Bayesian modeling.<\/a> Expert Systems with Applications 317:131862 (2024: IF: – 7.5)<\/strong><\/span><\/li>\n\n\n\n
    8. Dopiera\u0142a, P., Leszczy\u0144ski, W., \u0141\u0105czkowski, P., Pi\u0142ka, T., G\u00f3recki, T. <\/strong>(2026). Dynamic fatigue prediction in football: A deep learning-driven approach to optimize performance<\/a>. In B. Zielosko, R. Doro\u017c, I. Czarnowski, J. Kacprzyk & J. Ma\u0144dziuk (Eds.), Advances in Artificial Intelligence Research. PPRAI 2025. Springer, Cham. 361-373.<\/li>\n\n\n\n
    9. P. Kaczorek, J. S\u0142upski, F. Kornobis. M. Zar\u0119ba, T. G\u00f3recki<\/strong>, T. Pi\u0142ka (2026). Racing Beyond the Gate: Predicting Speedway Results with Expected Points (xP)<\/a>. In: Rios-Neto, H., Robberechts, P., Van Roy, M., Zimmermann, A. (eds), Machine Learning and Data Mining for Sports Analytics. MLSA 2025. Communications in Computer and Information Science, vol 2833. Springer, Cham. (Core A)<\/strong><\/span><\/li>\n\n\n\n
    10. Zar\u0229ba, M., Pi\u0142ka, T., G\u00f3recki, T.<\/strong>, Grzelak, B., Dyczkowski, K. (2025). Decoding defensive performance: a machine learning approach to football player valuation<\/a>. Journal of Big Data 12:275. (2024: IF: – 6.400)<\/strong><\/span><\/li>\n\n\n\n
    11. Grzelak, B., G\u00f3recki, T.<\/strong>, Dyczkowski, K. (2025). Evaluating Offensive and Defensive Performance in Football via Bayesian Techniques.<\/a> 5th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Zanzibar, Tanzania, 1-6.<\/li>\n\n\n\n
    12. Jamroziak, K., Iskierka-Jazdzewska, E., Robak, T., Zielonka, K., Giebel, S., Wi\u015bniewski, K., Drozd-Soko\u0142owska, J., Rybka, J., Piszczek, W., Joks, M., D\u0105browska-Iwanicka, A., Mital, A., Steckiewicz, P., Lech-Mara\u0144da, E., Jasi\u0144ski, M., Rymko, M., Marciniak, D., Wr\u00f3bel, T., Gil, L., Romejko-Jaro\u00adsi\u0144ska, J., Kruk-Kwapisz, D., Chudy, A., Machnicki, M., Giannopoulos, K., Stoklosa, T., G\u00f3recki, T.<\/strong>, & Pu\u0142a, B. (2025). Minimal residual disease-guided venetoclax plus rituximab for patients with previously untreated chronic lymphocytic leukemia (VERITA PALG-CLL5): primary endpoint analysis of the prospective, multicenter, Phase 2 trial<\/a>. Blood 146(Suppl. 1):5675-5676. (2024: IF: – 23.100)<\/strong><\/span><\/li>\n\n\n\n
    13. Chirkowska-Smolak, T., Garbacik, \u017b., Piorunek, M., Drabik-Podg\u00f3rna, V., G\u00f3recki, T.<\/strong>, & Sitarz, N. (2025). Organizational sources of academic burnout among university teaching students – towards a sustainable fit. Przegl\u0105d Bada\u0144 Edukacyjnych 57(2):75-94.<\/li>\n\n\n\n
    14. Sadurska, A., Zar\u0119ba, M., Pi\u0142ka, T. & G\u00f3recki, T.<\/strong> (2025). Leveraging GPS Data and Attention-based BiLSTM for Injury Prediction in Professional Football<\/a>. In I. Lukovi\u0107, S. Bjeladinovi\u0107, B. Deliba\u0161i\u0107, D. Bara\u0107, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia.<\/li>\n\n\n\n
    15. Zar\u0119ba, M., Pi\u0142ka, T. & G\u00f3recki, T.<\/strong> (2025). Gradient or Not? Predicting Football Action Sequences Using Boosting vs Neural Networks<\/a>. In I. Lukovi\u0107, S. Bjeladinovi\u0107, B. Deliba\u0161i\u0107, D. Bara\u0107, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia.<\/li>\n\n\n\n
    16. G\u00f3recki, T.<\/strong>, Krzy\u015bko, M., Wo\u0142y\u0144ski, W. (2025). Applying Classification Methods for Multivariate Functional Data<\/a>. In: Trejos, J., Chadjipadelis, T., Gran\u00e9, A., Villalobos, M. (eds) Data Science, Classification, and Artificial Intelligence for Modeling Decision Making. IFCS 2024. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. 99-105.<\/li>\n\n\n\n
    17. Tobin, G., Schuhmacher, A., G\u00f3recki, T.<\/strong>, Smaga, \u0141. (2025). The development and evaluation of multiple regression equations based on four common nutritional analysis packages to predict the metabolisable energy density of diets fed to grower\/finisher and adult pigs and their use for rat and mouse diets<\/a>. British Journal of Nutrition 133(4):433-455. (2024: IF: – 3.000)<\/strong><\/span><\/li>\n\n\n\n
    18. Eichner, J., Nowak, J., Grzelak, B., G\u00f3recki, T.<\/strong>, Pi\u0142ka, T., Dyczkowski, K. (2025). Advanced Vision Techniques in Soccer Match Analysis: From Detection to Classification<\/a>. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – Volume 3: VISAPP:808-815. (Multiconference)<\/span><\/strong><\/li>\n\n\n\n
    19. Piorunek, M., Chirkowska-Smolak, T., G\u00f3recki, T.<\/strong>, Garbacik, \u017b. (2024). Person-Centered Insights into Academic Burnout. New Educational Review 78(4):67-80.<\/li>\n\n\n\n
    20. \u0141a\u017aniewska, E., G\u00f3recki, T.<\/strong>, Kurowska-Pysz, J., Prytula, K., Plac, K. (2024). Resilience of the Polish labour market in regions bordering Ukraine in the context of the inflow of war refugees from Ukraine<\/a>. Wiadomo\u015bci statystyczne. The Polish Statistician 69(12):1-15.<\/li>\n\n\n\n
    21. Grzelak, B., G\u00f3recki, T.<\/strong>, Dyczkowski, K. (2024). Team Strengths via Bayesian Modeling<\/a>. 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Male, Maldives, 01-07.<\/li>\n\n\n\n
    22. Bartkowiak, M., Cyplik, P., G\u00f3recki, T.<\/strong>, Koralewski, A. (2024). Innovative Sales Forecasting: Utilizing Fuzzy Neural Networks for Enhanced Sales Prediction<\/a>. In B. Marcinkowski, A. Przybylek, A. Jarz\u0119bowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gda\u0144sk, Poland.<\/li>\n\n\n\n
    23. Zar\u0119ba, M., Pi\u0142ka, T., G\u00f3recki, T.<\/strong>, Grzelak, B., Dyczkowski, K. (2024). Improving The Evaluation of Defensive Player Values with Advanced Machine Learning Techniques.<\/a> In B. Marcinkowski, A. Przybylek, A. Jarz\u0119bowicz, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings). Gda\u0144sk, Poland.<\/li>\n\n\n\n
    24. K. Dyczkowski, B. Grzelak, T. G\u00f3recki<\/strong>, T. Pi\u0142ka, A. Sadurska, B. P\u0119kala, A.L. Owen (2024). Sensor-Based Injury Prediction in Football Using a New Interval-Valued Fuzzy Inference Library<\/a>. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Yokohama, Japan, 1-8. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    25. R. Kwieci\u0144ski, T. G\u00f3recki<\/strong>, A. Filipowska, V. Dubrov, V. (2024). Job Recommendations: Benchmarking of Collaborative Filtering Methods for Classifieds<\/a>. Electronics 13(15) 3049. (2023: IF: – 2.600)<\/strong><\/span><\/li>\n\n\n\n
    26. T. G\u00f3recki<\/strong>, M. \u0141uczak, P. Piasecki (2024). An exhaustive comparison of distance measures in the classification of time series with 1NN method<\/a>. Journal of Computational Science 76 (102235). (2023: IF: – 3.100)<\/strong><\/span><\/li>\n\n\n\n
    27. E. Kowal-Wisniewska, K. Jaskiewicz, A. Bartochowska et al. (2024). Towards effectiveness of cell-free DNA based liquid biopsy in head and neck squamous cell carcinoma<\/a>. Scientific Reports 14(2251). (2023: IF – 3.800)<\/strong><\/span><\/li>\n\n\n\n
    28. T. Chirkowska-Smolak, T. G\u00f3recki<\/strong>, M. Klakus, W. Metzger, M. Szargan (2023). The factorial validity of the Maslach Burnout Inventory: Student Survey (MBI-SS) in Poland<\/a>. Polish Psychological Bulletin 54(3):207-216.<\/li>\n\n\n\n
    29. E. \u0141a\u017aniewska, K. Plac, T. G\u00f3recki<\/strong>, J. Rykowski. (2023). Time to Rethink Energy: An Initiative towards Renewable and Smart Energy. A Comparative Analysis of Poland and Germany and Conclusions for Cross-Border Cooperation and Improving Resilience<\/a>. Barometr regionalny 19(2): 37-73.<\/li>\n\n\n\n
    30. E. \u0141a\u017aniewska, T. G\u00f3recki<\/strong>, J. Kurowska-Pysz, J. (2023). The impact of the Covid-19 pandemic on the resilience of the labour market in the Polish-German borderland<\/a>. Eastern Journal of European Studies 14(2):178-199. (2022: IF – 0.600)<\/strong><\/span><\/li>\n\n\n\n
    31. T. G\u00f3recki<\/strong>, M. \u0141uczak, P. Piasecki (2023). Similarity Forest for Time Series Classification<\/a>. Studies in Classification, Data Analysis, and Knowledge Organization: Classification and Data Science in the Digital Age 165-173.<\/li>\n\n\n\n
    32. A. Sadurska, T. Pi\u0142ka, B. Grzelak, T. G\u00f3recki<\/strong>, K. Dyczkowski, M. Zar\u0119ba (2023). Fusion of a Fuzzy Rule-Based Method and Other Decision-Making Models in Injury Prediction Problem in Football.<\/a> IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Incheon, Republic of Korea, 1-6. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    33. S. Pioro\u0144ski, T. G\u00f3recki<\/strong> (2023). Spotting Cyber Breaches in IoT Devices. Proceedings of the 18th Conference on Computer Science and Intelligence Systems<\/a>, M. Ganzha, L. Maciaszek, M. Paprzycki, D. \u015al\u0119zak (eds). ACSIS 35:1307-1310. (Multiconference)<\/span><\/strong><\/li>\n\n\n\n
    34. S. Pioro\u0144ski, T. G\u00f3recki<\/strong> (2023). Predicting Player Performance in Tactical Games with the Lightgbm Algorithm<\/a>. IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Brisbane, Australia, 22-27. (Core A)<\/span><\/strong><\/li>\n\n\n\n
    35. T. Chirkowska-Smolak, M. Piorunek, T. G\u00f3recki<\/strong>, \u017b. Garbacik, V. Drabik-Podg\u00f3rna, A. K\u0142awsiu\u0107-Zdu\u0144czyk (2023). Academic Burnout of Polish Students: A Latent Profile Analysis<\/a>. International Journal of Environmental Research and Public Health 20:4828. <\/li>\n\n\n\n
    36. R. Kwieci\u0144ski, G. Melniczak, T. G\u00f3recki<\/strong> (2023). Comparison of Real-Time and Batch Job Recommendations<\/a>. IEEE Access 11:20553-20559. (2022: IF – 3.900)<\/strong><\/span><\/li>\n\n\n\n
    37. E. Dorr, J.K., Hawes, T. G\u00f3recki<\/strong> et al. (2023). Food production and resource use of urban farms and gardens: a five-country study<\/a>. Agronomy for Sustainable Development 43(18). (2022: IF – 7.300)<\/strong><\/span><\/li>\n\n\n\n
    38. S. Pioro\u0144ski, T. G\u00f3recki<\/strong> (2023). Using GAN to Generate Malicious Samples Suitable for Binary Classifier Training<\/a>. 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 6522-6527. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    39. G. Silska, T. G\u00f3recki,<\/strong> (2023). Fiber Content of the Flax Germplasm (Linum usitatissimum<\/em> L.) Originating from Different Parts of the World<\/a>. Journal of Natural Fibers 20(1):2164108. (2022: IF – 3.500)<\/strong><\/span><\/li>\n\n\n\n
    40. T. Pi\u0142ka. B. Grzelak, A. Sadurska, T. G\u00f3recki<\/strong>, K. Dyczkowski (2023) Predicting Injuries in Football Based on Data Collected from GPS-Based Wearable Sensors<\/a>. Sensors 23:1227. (2022: IF – 3.900)<\/strong><\/span><\/li>\n\n\n\n
    41. T. Pi\u0142ka, B. Grzelak, A. Sadurska, T. G\u00f3recki<\/strong>, K. Dyczkowski (2022). Impact of changes in volumes of external training loads collected with wearable GPS sensors on the occurrence of injuries in football<\/a>. Book of abstracts: the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems (IPMU) \/ Boffa Stefania [i in.] (red.). Universit\u00e0 degli Studi di Milano-Bicocca 39-40.<\/li>\n\n\n\n
    42. G. Silska, T. G\u00f3recki<\/strong> (2022). Fiber Content in Stem and Fiber Yield in the Chosen Genetic Resources of Flax (Linum Usitatissimum<\/em> L.)<\/a>. Journal of Natural Fibers 19(4):9693-9718. (2021: IF – 3.507)<\/strong><\/span><\/li>\n\n\n\n
    43. G. Silska, M. Mackiewicz-Talarczyk, T. G\u00f3recki<\/strong> (2022). Valorization and Analysis of Flax Traits in Selected Accessions of Diversified Origin from the Linum usitatissimum<\/em> L<\/a>. Genetic Resources Collection. Journal of Natural Fibers 19(17):15984-16004. (2021: IF – 3.507)<\/strong><\/span><\/li>\n\n\n\n
    44. M. Niewiarowicz, A. Wicher, A., S\u0119k, T. G\u00f3recki<\/strong> (2022). Speech intelligibility deterioration for normal hearing and hearing impaired patients with different types of tinnitus<\/a>. Speech Communication (139):35-44. (2021: IF – 2.723)<\/strong><\/span><\/li>\n\n\n\n
    45. R. Kwieci\u0144ski, T. G\u00f3recki<\/strong>, A. Filipowska (2022). Learning edge importance in bipartite graph-based recommendations<\/a>. Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. \u015al\u0119zak (eds). ACSIS 30: 227-233. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    46. S. Pioro\u0144ski, T. G\u00f3recki<\/strong> (2022). Using gradient boosting trees to predict the costs of forwarding contracts<\/a>. Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. \u015al\u0119zak (eds). ACSIS 30:421-424. (Core B)<\/strong><\/span><\/li>\n\n\n\n
    47. E. \u0141a\u017aniewska, T. G\u00f3recki<\/strong>, K. P\u0142ac (2022). Regional labour markets as a result of the impact of the COVID-19 Pandemic\u2014A Polish-German Borderland Case Study<\/a>. In: Jajuga, K., Dehnel, G., Walesiak, M. (eds) Modern Classification and Data Analysis. SKAD 2021. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham.<\/li>\n\n\n\n
    48. E. \u0141a\u017aniewska, I. Janicka, T. G\u00f3recki (2021). Kryteria oceny aktywno\u015bci gmin przygranicznych w kierunku \u201egreen smart city\u201d<\/a>. Rocznik Integracji Europejskiej (15):195-213.<\/li>\n\n\n\n
    49. E. \u0141a\u017aniewska, I. Janicka, T. G\u00f3recki<\/strong> (2021). Co-creation of the green smart city concept. Analysis of the maturity of municipalities in the Polish-German borderland region<\/a>. TeMA. Journal of Land Use, Mobility and Environment 14(3):319-342.<\/li>\n\n\n\n
    50. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, W. Wo\u0142y\u0144ski (2021). Measuring and Testing Mutual Dependence for Functional Data<\/a>. In: Chadjipadelis T., Lausen B., Markos A., Lee T.R., Montanari A., Nugent R. (eds) Data Analysis and Rationality in a Complex World. IFCS 2019. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. 65-73.<\/li>\n\n\n\n
    51. \u0141. Borchmann, D. Jurkiewicz, F. Grali\u0144ski, T. G\u00f3recki<\/strong> (2021). Dynamic Boundary Time Warping for sub-sequence matching with few examples<\/a>. Expert Systems with Applications 169:114344. (2020: IF – 6.954)<\/strong><\/span><\/li>\n\n\n\n
    52. K. W\u0142odarska, P. Piasecki, A. Lobo-Prieto, K. Pawlak-Lema\u0144ska, T. G\u00f3recki<\/strong>, E. Sikorska (2021). Rapid screening of apple juice quality using ultraviolet, visible, and near infrared spectroscopy and chemometrics: A comparative study<\/a>. Microchemical Journal 164:106051. (2020: IF – 4.821)<\/strong><\/span><\/li>\n\n\n\n
    53. E. \u0141a\u017aniewska, I. Janicka, T. G\u00f3recki<\/strong> (2021). Green Smart City as a New Paradigm of Local Development<\/a>. Problemy ekorozwoju 16(2):125-136. (2020: IF – 0.859)<\/strong><\/span><\/li>\n\n\n\n
    54. E. \u0141a\u017aniewska, I. Janicka, T. G\u00f3recki<\/strong> (2021). Aktywno\u015b\u0107 ekologiczna gmin z perspektywy transgranicznej na przyk\u0142adzie gmin pogranicza polsko-niemieckiego<\/a>. Studia Regionalne i Lokalne 84(2).<\/li>\n\n\n\n
    55. M. Bosiacki, L. Bednorz, K. Fede\u0144czak, T. G\u00f3recki<\/strong>, A. Mizgajski, L. Poni\u017cy, T. Spi\u017cewski (2021). Soil Quality as a Key Factor in Producing Vegetables for Home Consumption\u2014A Case Study of Urban Allotments in Gorz\u00f3w Wielkopolski (Poland)<\/a>. Agronomy 11(9):1836. (2020: IF – 3.417)<\/strong><\/span><\/li>\n\n\n\n
    56. T. G\u00f3recki<\/strong>, L. Horv\u00e1th, P. Kokoszka (2020). Tests of Normality of Functional Data<\/a>. International Statistical Review 88(3):677-697. (2019: IF – 2.740)<\/strong><\/span><\/li>\n\n\n\n
    57. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, W. Wo\u0142y\u0144ski (2020). Variable Selection for Classification of Multivariate Functional Data<\/a>. In: Imaizumi T., Okada A., Miyamoto S., Sakaori F., Yamamoto Y., Vichi M. (eds) Advanced Studies in Classification and Data Science. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Singapore. 215-225.<\/li>\n\n\n\n
    58. T. Go\u0301recki<\/strong>, M. Jakubus, M. Krzys\u0301ko, W. Wo\u0142yn\u0301ski (2020). Application of Distance Covariance in Selection of Nutrients During Dynamic Process of Sewage Sludge Conditioning with Bio-preparation<\/a>. Waste and Biomass Valorization 11(8):4157-4166. (2019: IF – 2.851)<\/strong><\/span><\/li>\n\n\n\n
    59. T. Go\u0301recki<\/strong>, M. Krzys\u0301ko, W. Wo\u0142yn\u0301ski (2020). Independence test and canonical correlation analysis based on the alignment between kernel matrices for multivariate functional data<\/a>. Artificial Intelligence Review 53(1):475-499. (2019: IF – 5.747)<\/strong><\/span><\/li>\n\n\n\n
    60. T. G\u00f3recki<\/strong>, P. Piasecki (2020). Generalization of the Procrustes coefficient to functional data<\/a>. Communications in Statistics – Simulation and Computation 49(3):808-816. (2019: IF – 0.651)<\/strong><\/span><\/li>\n\n\n\n
    61. T. Go\u0301recki<\/strong>, M. Krzys\u0301ko, W. Wo\u0142yn\u0301ski (2020). Generalized canonical correlation analysis for functional data<\/a>. Biometrical Letters 57(1):1-12.<\/li>\n\n\n\n
    62. T. G\u00f3recki<\/strong>, P. Piasecki (2019). RAndom Neural Networks (RANNs): a new general classifier inspired by Random Forest<\/a>. Proceedings of PP-RAI\u20192019 68-72.<\/li>\n\n\n\n
    63. E. Sikorska, K. W\u00f3jcicki, W. Kozak, A. Gliszczy\u0144ska-\u015awig\u0142o, I. Khmelinskii, T. G\u00f3recki<\/strong>, F. Caponio , V.M. Paradiso, C. Summo, A. Pasqualone (2019). Front-Face Fluorescence Spectroscopy and Chemometrics for Quality Control of Cold-Pressed Rapeseed Oil During Storage<\/a>. Foods 8(12):665. (2018: IF – 3.011)<\/strong><\/span><\/li>\n\n\n\n
    64. K. W\u0142odarska, K. Pawlak-Lema\u0144ska, T. G\u00f3recki<\/strong>, E. Sikorska. (2019) Factors Influencing Consumers\u2019 Perceptions of Food: A Study of Apple Juice Using Sensory and Visual Attention Methods<\/a>. Foods 8:545. (2018: IF – 3.011)<\/strong><\/span><\/li>\n\n\n\n
    65. T. G\u00f3recki<\/strong>, P. Piasecki (2019). A Comprehensive Comparison of Distance Measures for Time Series Classification.<\/a> Steland, A., Rafaj\u0142owicz, E., Okhrin, O. (eds.) Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics and Statistics 294:409-428.<\/li>\n\n\n\n
    66. T. G\u00f3recki<\/strong>, \u0141. Smaga (2019). fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data<\/a>. Computational Statistics 34(2):571-597. (2018: IF – 0.680)<\/strong><\/span><\/li>\n\n\n\n
    67. T. G\u00f3recki<\/strong>, M. \u0141uczak (2019). The influence of the Sakoe\u2013Chiba band size on time series classification<\/a>. Journal of Intelligent & Fuzzy Systems 36(1):527-539. (2018: IF – 1.637)<\/strong><\/span><\/li>\n\n\n\n
    68. T. Go\u0301recki<\/strong>, M. Krzys\u0301ko M., W. Wo\u0142yn\u0301ski (2019). Variable selection in multivariate functional data classification<\/a>. Statistics in Transition 20(2):123-138.<\/li>\n\n\n\n
    69. F. Grali\u0144ski, A. Wr\u00f3blewska, T. Stanis\u0142awek, K. Grabowski, T. G\u00f3recki<\/strong> (2019). GEval: Tool for Debugging NLP Datasets and Models<\/a>. Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP 254-262. (Core A*)<\/strong><\/span><\/li>\n\n\n\n
    70. T. G\u00f3recki<\/strong>, L. Horv\u00e1th, P. Kokoszka (2018). Change point detection in heteroscedastic time series<\/a>. Econometrics and Statistics 7:63-88.<\/li>\n\n\n\n
    71. T. G\u00f3recki<\/strong>, S. H\u00f6rmann, L. Horv\u00e1th, P. Kokoszka (2018). Testing normality of functional time series<\/a>. Journal of Time Series Analysis 39(4):471-487. (2017: IF – 0.826)<\/strong><\/span><\/li>\n\n\n\n
    72. T. G\u00f3recki, <\/strong>M. Krzy\u015bko, \u0141. Waszak, W. Wo\u0142y\u0144ski (2018). Selected statistical methods of data analysis for multivariate functional data<\/a>. Statistical Papers, 59(1):153-182. (2017: IF – 1.024)<\/strong><\/span><\/li>\n\n\n\n
    73. T. G\u00f3recki,<\/strong> M. Krzy\u015bko, W. Wo\u0142y\u0144ski (2018). Dynamic dependence between infrastructure and market size in European countries, In: Babiak J., Kisio\u0142ek A., Iwa\u0144czuk-Kaliska A., Urbaniak K. (eds), Studies of economic and social processes. Selected aspects of contemporary economy, The Great Poland University of Social and Economics in \u015aroda Wlkp. 105-122.<\/li>\n\n\n\n
    74. T. G\u00f3recki<\/strong> (2018). Classification of time series using combination of DTW and LCSS dissimilarity measures<\/a>. Communications in Statistics – Simulation and Computation 47(1):263-276. (2017: IF – 0.501)<\/span><\/strong><\/li>\n\n\n\n
    75. T. G\u00f3recki<\/strong>, P. Piasecki (2018). An experimental evaluation of time series classification using various distance measures<\/a>. Archives of Data Science, Series A 5(1):1-25.<\/li>\n\n\n\n
    76. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, W. Wo\u0142y\u0144ski (2017). Correlation analysis for multivariate functional data<\/a>. Studies in Classification, Data Analysis, and Knowledge Organization:Data Science 243-258.<\/li>\n\n\n\n
    77. T. G\u00f3recki<\/strong>, \u0141. Smaga (2017). Multivariate analysis of variance for functional data<\/a>. Journal of Applied Statistics 44(12): 2172-2189. (2016: IF – 0.664)<\/span><\/strong><\/span><\/span><\/span><\/li>\n\n\n\n
    78. K. W\u0142odarska, K. Pawlak-Lema\u0144ska, <\/span>T. G\u00f3recki<\/strong>, E. Sikorska (2017). <\/span>Classification of commercial apple juices based on multivariate analysis of their chemical profiles.<\/a> International Journal of Food Properties 20(8): 1773-1785. <\/span>(2016: IF – 1.427)<\/span><\/strong><\/span><\/li>\n\n\n\n
    79. T. G\u00f3recki<\/strong>, M. \u0141uczak (2017). Stacked regression with a generalization of the Moore-Penrose pseudoinverse<\/a>. Statistics in Transition 18(3): 443-458.<\/li>\n\n\n\n
    80. K. W\u0142odarska, K. Pawlak-Lema\u0144ska, T. G\u00f3recki<\/strong>, E. Sikorska (2016). Perception of apple juice: a comparison of physicochemical measurements, descriptive analysis and consumer responses.<\/a> Journal of Food Quality 39(4):351-361. (2015: IF – 0.755)<\/span><\/strong><\/span><\/li>\n\n\n\n
    81. T. G\u00f3recki<\/strong>, M. \u0141uczak (2016). <\/span>Evolutionarily tuned generalized pseudo-inverse in linear discriminant analysis<\/a>. Computing and Informatics 35(3):615-634. (2015: IF – 0.524)<\/span><\/strong><\/li>\n\n\n\n
    82. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, \u0141. Waszak, W. Wo\u0142y\u0144ski (2016). Multivariate functional regression analysis with application to classification problems<\/a>. Studies in Classification, Data Analysis, and Knowledge Organization: Analysis of Large and Complex Data 173-183.<\/li>\n\n\n\n
    83. T. G\u00f3recki<\/strong>, M. Krzy\u015bko., W. Ratajczak, W. Wo\u0142y\u0144ski (2016). An extension of the classical distance correlation coefficient for multivariate functional data with applications<\/a>. Statistics in Transition 17(3):449-466.<\/li>\n\n\n\n
    84. K. W\u0142odarska, K. Pawlak-Lema\u0144ska, T. G\u00f3recki<\/strong>, E. Sikorska (2015). Motywy wyboru \u017cywno\u015bci przez konsument\u00f3w – badania pilota\u017cowe.<\/a> Journal of Agribusiness and Rural Development 4(38):839-847.<\/li>\n\n\n\n
    85. T. G\u00f3recki,<\/strong> \u0141. Smaga (2015). A comparison of tests for the one-way ANOVA problem for functional data<\/a>. Computational Statistics 30(4):987-1010. (2014: IF – 0.403)<\/strong><\/span><\/li>\n\n\n\n
    86. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, W. Wo\u0142y\u0144ski (2015). Classification problems based on regression models for multi-dimensional functional data.<\/a> Statistics in Transition 16(1):97-110.<\/li>\n\n\n\n
    87. T. G\u00f3recki<\/strong> (2015). Sequential combining in discriminant analysis.<\/a> Journal of Applied Statistics 42(2):398-408. (2014: IF – 0.417)<\/span><\/strong><\/li>\n\n\n\n
    88. T. G\u00f3recki<\/strong>, M. \u0141uczak (2015). Multivariate time series classification with parametric derivative dynamic time warping.<\/a> Expert Systems with Applications 42(5):2305-2312. (2014: IF – 2.240)<\/span><\/strong><\/li>\n\n\n\n
    89. T. G\u00f3recki<\/strong>, M. Krzy\u015bko (2015). Regression methods for combining multiple classifiers.<\/a> Communications in Statistics – Simulation and Computation 44(3):739-755. (2014: IF – 0.325)<\/span><\/strong><\/li>\n\n\n\n
    90. T. G\u00f3recki<\/strong>, M. Krzy\u015bko (2014). A learning algorithm combining functional discriminant coordinates and functional principal components.<\/a> Discussiones Mathematicae Probability and Statistics 34(1-2):127-141.<\/li>\n\n\n\n
    91. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, \u0141. Waszak, W. Wo\u0142y\u0144ski (2014). Methods of reducing dimension for functional data<\/a>. Statistics in Transition 15(2):231-242.<\/li>\n\n\n\n
    92. T. G\u00f3recki<\/strong>, M. \u0141uczak (2014). A variant of gravitational classification<\/a>. Biometrical Letters 51(1):1-12.<\/li>\n\n\n\n
    93. T. G\u00f3recki<\/strong> (2014). Using derivatives in a longest common subsequence dissimilarity measure for time series classification<\/a>. Pattern Recognition Letters 45C:99-105. (2013: IF – 1.062)<\/span><\/strong><\/li>\n\n\n\n
    94. T. G\u00f3recki<\/strong>, M. \u0141uczak (2014). Non-isometric transforms in time series classification using DTW<\/a>. Knowledge-Based Systems 61:98-108. (2013: IF – 3.058)<\/span><\/strong><\/li>\n\n\n\n
    95. T. G\u00f3recki<\/strong>, M. \u0141uczak (2014). First and second derivative in time series classification using DTW.<\/a> Communications in Statistics – Simulation and Computation 43(9):2081-2092. (2013: IF – 0.288)<\/span><\/strong><\/li>\n\n\n\n
    96. T. G\u00f3recki<\/strong>, M. Krzy\u015bko, \u0141. Waszak (2014). Functional Discriminant Coordinates<\/a>. Communications in Statistics – Theory and Methods 43(5):1013-1025. (2013: IF – 0.289)<\/span><\/strong><\/span><\/li>\n\n\n\n
    97. M. Krzy\u015bko, A. Derejko, T. G\u00f3recki<\/strong>, E. Gacek (2013). Principal component analysis for functional data on grain yield of winter wheat cultivars<\/a>. Biometrical Letters 50(2):81-94.<\/span><\/li>\n\n\n\n
    98. T. G\u00f3recki<\/strong>, E. \u0141a\u017aniewska (2013). Funkcjonalna analiza sk\u0142adowych g\u0142\u00f3wnych PKB<\/a>. Wiadomo\u015bci Statystyczne 4:23-34.<\/span><\/li>\n\n\n\n
    99. T. G\u00f3recki<\/strong>, M. \u0141uczak (2013). Linear discriminant analysis with a generalization of the Moore-Penrose pseudoinverse<\/a>. International Journal of Applied Mathematics and Computer Science 23(2):463-471. (2012: IF – 1.008)<\/span><\/strong><\/span><\/li>\n\n\n\n
    100. T. G\u00f3recki <\/strong>(2013).<\/span> Sequential correction of linear classifiers<\/a>. Journal of Applied Statistics 40(4):763-776. (2012: IF – 0.449)<\/span><\/strong> <\/span><\/li>\n\n\n\n
    101. T. G\u00f3recki<\/strong>, M. \u0141uczak (2013). Using derivatives in time series classification<\/a>. Data Mining and Knowledge Discovery 26(2):310-331. (2012: IF – 2.877)<\/span><\/strong> <\/span><\/span><\/li>\n\n\n\n
    102. T. G\u00f3recki<\/strong>, M. Krzy\u015bko (2012). <\/span>A kernel version of functional principal components analysis<\/a>. Statistics in Transition 13(3):559-568.<\/span><\/li>\n\n\n\n
    103. E. \u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2012). Regional specialization and concentration in Poland in the period 1996-2008 on the basis of GVA. In: Statistical methods in analyses of economic phenomena under integration and globalization (eds. P. Cmala, K. Kruszy\u0144ski), Zak\u0142ad Wydawnictw Statystycznych 139-155.<\/li>\n\n\n\n
    104. M. Naro\u017cny, T. G\u00f3recki<\/strong>, K. Eitner, W. Urbaniak, S. Lipiecka, K. Szefli\u0144ska (2012). Measurements of PM10 and PM2.5 particle concentrations in Pozna\u0144, Poland. In: Proceedings of the 39th International <\/span>Conference of Slovak Society of Chemical Engineering, Tatransk\u00e9 Matliare, Slovakia (eds. J. Marko\u0161) 298-310.<\/span><\/span><\/span><\/li>\n\n\n\n
    105. E. \u0141a\u017aniewska, T. G\u00f3recki<\/strong>, R. Chmielewski (2012). Problemy metodologiczne budowy wska\u017anik\u00f3w i indeks\u00f3w konkurencyjno\u015bci<\/a>. In: Konkurencyjno\u015b\u0107 regionalna (eds. E. \u0141a\u017aniewska, M. Gorynia) Wydawnictwo Naukowe PWN 72-88.<\/span><\/li>\n\n\n\n
    106. E. \u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2012). Analiza konwergencji podregion\u00f3w za pomoc\u0105 \u0142a\u0144cuch\u00f3w Markowa<\/a>. Wiadomo\u015bci Statystyczne 5:1-10.<\/li>\n\n\n\n
    107. T. G\u00f3recki <\/strong>(2012). Two parametrical derivative dynamic time warping. In: Data analysis methods and its applications (eds. J. Pociecha, R. Decker) C.H. Beck <\/span>31-40.<\/li>\n\n\n\n
    108. T. G\u00f3recki<\/strong>, M. Krzy\u015bko (2012). Functional Principal Components Analysis. In: Data analysis methods and its applications (eds. J. Pociecha, R. Decker) C.H. Beck 71-87.<\/li>\n\n\n\n
    109. T. G\u00f3recki<\/strong>, M. \u0141uczak (2010). Some methods of constructing kernels in statistical learning<\/a>. Discussiones Mathematicae Probability and Statistics 30(2):179-201.<\/li>\n\n\n\n
    110. T. G\u00f3recki<\/strong>, M. \u0141uczak (2010). Some methods of replacing the nearest neighbor method<\/a>. Communications in Statistics-Simulation and Computation 39:262-276. (2009: IF – 0.383)<\/span><\/strong><\/li>\n\n\n\n
    111. E. Sikorska, T. G\u00f3recki<\/strong>, I. Khmelinskii, M. Sikorski (2009). Evaluation of beer aging using its autofluorescence. Acta Horticulturae (ISHS) 848:299-306.<\/li>\n\n\n\n
    112. J. Chmielewski, T. G\u00f3recki<\/strong>, M. Sikorski, E. Sikorska (2009), Zastosowania elektronicznego nosa w badaniach procesu starzenia piw. In: Chemometria w nauce i praktyce, red. D. Zuba, A. Parczewski, Wydawnictwo Instytutu Ekspertyz S\u0105dowych 137-144.<\/li>\n\n\n\n
    113. E. \u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2008). Rozw\u00f3j gospodarczy polskich region\u00f3w na podstawie analizy shift-share w latach 1999-2004. In: Sp\u00f3jno\u015b\u0107 czy konkurencyjno\u015b\u0107-dylemat polityki Unii Europejskiej, M. Klamut (red.), Prace Naukowe nr 19 Uniwersytetu Ekonomicznego we Wroc\u0142awiu 187-197.<\/li>\n\n\n\n
    114. E. \u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2008). Analiza sektorowej specjalizacji struktury regionalnej produkcji w Polsce w oparciu o zatrudnienie. In:  Problemy wsp\u00f3\u0142pracy gospodarczej w regionie ba\u0142tyckim w kontek\u015bcie integracji europejskiej, A. Ignasiak-Szulc, W. Kosiedowski (red.), Towarzystwo Naukowe Organizacji i Kierownictwa, Toru\u0144 167-176.<\/li>\n\n\n\n
    115. E. \u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2008). Identyfikacja i analiza proces\u00f3w koncentracji i specjalizacji oraz polaryzacji rozwoju spo\u0142eczno-gospodarczego w uk\u0142adzie regionalnym Polski w latach 1999-2005 w przekroju jednostek NUTS-2 ze szczeg\u00f3lnym uwzgl\u0119dnieniem pogranicza zachodniego Polski. In: Gospodarka lokalna i regionalna w teorii i praktyce, R. Brol (red.), Prace Naukowe nr 3 (1203) Uniwersytetu Ekonomicznego we Wroc\u0142awiu 177-189.<\/li>\n\n\n\n
    116. J. Chmielewski, E. Sikorska, T. G\u00f3recki<\/strong>, I. Khmelinskii, M. Sikorski (2007).<\/span> Evaluation of beer aging using an elecronic nose. Polish Journal of Food and Nutrition Sciences 57(4):91-93.<\/li>\n\n\n\n
    117. J. Chmielewski, E. Sikorska, T. Gorecki<\/strong>, I. V. Khmelinskii and M. Sikorski (2007). <\/span>Flavour analysis of edible oils by a sensor-array electronic nose. In: Current Trends in Commodity Science, II, (eds. R. Zielinski and D. Wieczorek), The Poznan University of Economics Publishing House, Poznan 765-770.<\/li>\n\n\n\n
    118. E. Sikorska, J. Chmielewski, T. G\u00f3recki<\/strong>, I. Khmelinskii, M. Sikorski, and D. De Keukeleire (2007). <\/span>Discrimination of beer flavours by analysis of volatiles using the mass spectrometer as an electronic nose. Journal of the Institute of Brewing 113(1):110-116. (2006: IF – 1.012)<\/span><\/strong><\/li>\n\n\n\n
    119. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2006). Shifts in the regional development in Poland in the transformation period 1990-2001<\/a>. Prace Naukowe XII\/2006, ACC Journal 138-145.<\/li>\n\n\n\n
    120. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2006). Regional development assessment methods on the basis of Michalski?s taxonomic method<\/a>. Prace Naukowe XII\/2006, ACC Journal 129-137.<\/li>\n\n\n\n
    121. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2006). Procesy konwergencji i dywergencji-prezentacja wybranych modeli wykorzystywanych w analizach regionalnych. Prace Naukowe nr 1099 AE Wroc\u0142aw. Sp\u00f3jno\u015b\u0107 spo\u0142eczna, gospodarcza i terytorialna w polityce UE 293-302.<\/li>\n\n\n\n
    122. E. Sikorska, J. Chmielewski, T. G\u00f3recki<\/strong>, I. Khmelinskii, M. Insi\u0144ska, Rak, E. Dulewicz, and M. Sikorski (2006). Comparison of fluorescence spectroscopy and headspace mass spectrometry electronic nose used to analyze changes in beer during storage. In: Proceedings of the 15th IGWT Symposium, Global safety of commodity and environment. Quality of life, Volume I, Kyiv, Ukraine 519-524.<\/li>\n\n\n\n
    123. E. Sikorska, T. G\u00f3recki<\/strong>, I. V. Khmelinskii, M. Sikorski, D. Keukeleire (2006). Monitoring beer during storage by fluorescence spectroscopy. Food Chemistry 96(4):632-639. (2005: IF – 2.433)<\/span><\/strong><\/li>\n\n\n\n
    124. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2005). Metody bada\u0144 przestrzenno-ekonomicznych w uj\u0119ciu dynamicznym i ich zastosowanie w regionalistyce. Wizualizacja zjawisk.<\/a> Studia Regionalne i Lokalne 2(20):91-101.<\/li>\n\n\n\n
    125. J. Chmielewski, E. Sikorska, T. G\u00f3recki<\/strong>, I. Khmelinskii, G. Nowacka, M. Sikorski and J. Kozio\u0142 (2005). Discrimination of beer flavours by headspace mass spectrometer artificial nose. In: Proceedings of the 8th International Commodity Science Conference (IGWT), Current trends in commodity science, Volume II, Pozna\u0144, Poland 955-960.<\/li>\n\n\n\n
    126. T. G\u00f3recki <\/strong>(2005). Effect of choice of dissimilarity measure on classification efficiency with nearest neighbor method<\/a>. Discussiones Mathematicae Probability and Statistics 25(2):217-239.<\/li>\n\n\n\n
    127. T. G\u00f3recki <\/strong>(2005). Stacked regression with restrictions<\/a>. Discussiones Mathematicae Probability and Statistics 25(1):103-113.<\/li>\n\n\n\n
    128. E. Sikorska, T. G\u00f3recki<\/strong>, Igor V. Khmelinskii, M. Sikorski, J. Kozio\u0142 (2005). Classification of edible oils using synchronous scanning fluorescence spectroscopy. Food Chemistry 89(2):217-225. (2004: IF – 1.811)<\/span><\/strong><\/li>\n\n\n\n
    129. E. Sikorska, T. G\u00f3recki<\/strong>, I. V. Khmelinskii, M. Sikorski, D. Keukeleire (2004). Fluorescence spectroscopy for characterization and differentiation of beers. Journal of the Institute of Brewing 110(4):267-275. (2003: IF – 0.536)<\/span><\/strong><\/li>\n\n\n\n
    130. E. Sikorska, T. G\u00f3recki<\/strong>, I. V. Khmelinskii, M. Sikorski, J. Kozio\u0142 (2004). Application of fluorescence in food analysis. In: <\/span>Proceedings of the 14th IGWT Symposium, Focusing new Century: Commodity, Trade, Environment, Volume I, Beijing, China 172-176.<\/li>\n\n\n\n
    131. E. Sikorska, T. G\u00f3recki<\/strong>, I. V. Khmelinskii, M. Sikorski (2004). Investigation of beers by synchronous scanning fluorescence spectroscopy. In: Proceedings of the 14th IGWT Symposium, Focusing new Century: Commodity, Trade, Environment, Volume I, Beijing, China 167-171.<\/li>\n\n\n\n
    132. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2004). Mo\u017cliwo\u015bci wizualizacji danych wielowymiarowych. Wiadomo\u015bci statystyczne 12:63-71.<\/li>\n\n\n\n
    133. E. Nowi\u0144ska-\u0141a\u017aniewska, T. G\u00f3recki <\/strong>(2004). Metody wizualizacji danych w badaniach regionalnych. Wiadomo\u015bci Statystyczne 8:63-69.<\/li>\n<\/ol>\n\n\n\n
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      C. Prace popularnonaukowe<\/strong><\/p>\n\n\n\n

        \n
      1. W. Urbaniak, M. Naro\u017cny, T. G\u00f3recki<\/strong>, K. Eitner, S. Lipiecka-S\u0119k (2015). Rozk\u0142ad st\u0119\u017ce\u0144 py\u0142u zawieszonego PM10 w Poznaniu. Przegl\u0105d komunalny 5:73-74.<\/li>\n\n\n\n
      2. M. Naro\u017cny, K. Eitner, W. Urbaniak, T. G\u00f3recki <\/strong>(2012). Zapylenie w Polsce. Przegl\u0105d komunalny 4:16-18.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

        A. Monografie B. Prace naukowe C. Prace popularnonaukowe<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/pages\/13"}],"collection":[{"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=13"}],"version-history":[{"count":180,"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/pages\/13\/revisions"}],"predecessor-version":[{"id":770,"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=\/wp\/v2\/pages\/13\/revisions\/770"}],"wp:attachment":[{"href":"http:\/\/drizzt.home.amu.edu.pl\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}