166,717 research outputs found
Reverend John J. Majewski
No full textPortrait of Reverend John J. Majewski. Mounted and signed: "To W.A. Keleher, Gratefully yours, Rev. John J. Majewski." Date unknown
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Intelligent opinion mining and sentiment analysis using artificial neural networks
No full textThe article formulates a rigorously developed concept of opinion mining and sentiment analysis using hybrid neural networks. This conceptual method for processing natural-language text enables a variety of analyses of the subjective content of texts. It is a methodology based on hybrid neural networks for detecting subjective content and potential opinions, as well as a method which allows us to classify different opinion type and sentiment score classes. Moreover, a general processing scheme, using neural networks, for sentiment and opinion analysis has been presented. Furthermore, a methodology which allows us to determine sentiment regression has been devised. The paper proposes a method for classification of the text being examined based on the amount of positive, neutral or negative opinion it contains. The research presented here offers the possibility of motivating and inspiring further development of the methods that have been elaborated in this paper.Stuart, KDC.; Majewski, M. (2015). Intelligent opinion mining and sentiment analysis using artificial neural networks. Lecture Notes in Computer Science. 9492:103-110. doi:10.1007/978-3-319-26561-2_13S1031109492Feldman, R.: Techniques and applications for sentiment analysis. Commun. ACM 56(4), 82–89 (2013)Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011)Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013)Chen, H., Zimbra, D.: AI and opinion mining. IEEE Intell. Syst. 25(3), 74–80 (2010)Majewski, M., Zurada, J.M.: Sentence recognition using artificial neural networks. Knowl. Based Syst. 21(7), 629–635 (2008)Kacalak, W., Stuart, K.D., Majewski, M.: Intelligent natural language processing. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds.) ICNC 2006. LNCS, vol. 4221, pp. 584–587. Springer, Heidelberg (2006)Kacalak, W., Stuart, K., Majewski, M.: Selected problems of intelligent handwriting recognition. In: Melin, P., Castillo, O., Ramírez, E.G., Kacprzyk, J., Pedrycz, W. (eds.) IFSA 2007. Advances in Soft Computing, vol. 41, pp. 298–305. Springer, Cancun (2007)Stuart, K.D., Majewski, M.: Selected problems of knowledge discovery using artificial neural networks. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds.) ISNN 2007, Part III. LNCS, vol. 4493, pp. 1049–1057. Springer, Heidelberg (2007)Stuart, K., Majewski, M.: A new method for intelligent knowledge discovery. In: Castillo, O., Melin, P., Ross, O.M., Cruz, R.S., Pedrycz, W., Kacprzyk, J. (eds.) IFSA 2007. Advances in Soft Computing, vol. 42, pp. 721–729. Springer, Heidelberg (2007)Stuart, K.D., Majewski, M.: Artificial creativity in linguistics using evolvable fuzzy neural networks. In: Hornby, G.S., Sekanina, L., Haddow, P.C. (eds.) ICES 2008. LNCS, vol. 5216, pp. 437–442. Springer, Heidelberg (2008)Stuart, K.D., Majewski, M.: Evolvable neuro-fuzzy system for artificial creativity in linguistics. In: Huang, D.-S., Wunsch II, D.C., Levine, D.S., Jo, K.-H. (eds.) ICIC 2008. LNCS (LNAI), vol. 5227, pp. 46–53. Springer, Heidelberg (2008)Stuart, K.D., Majewski, M., Trelis, A.B.: Selected problems of intelligent corpus analysis through probabilistic neural networks. In: Zhang, L., Lu, B.-L., Kwok, J. (eds.) ISNN 2010, Part II. LNCS, vol. 6064, pp. 268–275. Springer, Heidelberg (2010)Stuart, K.D., Majewski, M., Trelis, A.B.: Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds.) ISNN 2011, Part I. LNCS, vol. 6675, pp. 83–92. Springer, Heidelberg (2011)Specht, D.F.: Probabilistic neural networks. Neural Netw. 3(1), 109–118 (1990)Specht, D.F.: A general regression neural network. IEEE Trans. Neural Netw. 2(6), 568–576 (1991
Pacific States Marine Fisheries Commission
No full textHeery, E., Bellman, M.A., and J. Majewski. 2010. Pacific halibut bycatch in the U.S. west coas
HIGH-J LINES IN THE BAND OF
No full text J. K. G. Watson, S. C. Poster, A. R. W. McKellar, P. Bernath, T. Amano, F. S. Pan, M. W. Crofton, R. S. Altman, and T. Oka, Can. J. Phys. 62, 1875 (1984) Address of Majewski: Department of Chemistry, University of Pittsburgh, Pittsburgh PA 15260. Address of Marshall, McKellar, and Watson: Herzberg Institute of Astrophysics, National Reserch Council of Canada, Ottawa, Ontario, Canada KIA OR6.Author Institution:This paper reports on the analysis of the high-J emission lines of the band of described at last year's Symposium, together with new absorption measurements using diode laser sources and the same type of hollow-cathode cell that have confirmed some of the emission measurments and extended them to lower wavenumbers. These high-J lines show clearly the effects of the perturbation of the state by the state, even although the pure vibrational separtion between them is about . Pits of these data together with the lower-J , using both effective Hamiltonian and supermatrix models that include the interaction explicitly, will be reported
NEW INFRARED OBSERVATIONS OF THE MOLECULE
No full textAuthor Institution: Department of Chemistry, University of Pittsburgh; Herzberg Institute of Astrophysics, National Research Council of CanadaThe new hollow-cathode discharge source described at previous Symposia1 gives many infrared lines of the neutral molecule as well as of the vibration-rotation spectrum of the . The former are mostly lines of the known and electronic , but the higher rotational temperature in the new source makes it possible to extend the previous assignments to higher N levels. The quality of the fit of the spectrum is not significantly improved by introducing additional parameters, suggesting that there are many small but irregular perturbations. A new group of lines near 4300 cm-1 is assigned to the electronic transition , This is the first observation of an state of . papers TE7 (1985) and RE5 (1986). W.A. Majewski, M.D. Marshall, A.R.W. McKellar, J.W.C. Johns, and J.K.G. Watson, J. Mol. Spectrosc., in press. G. Herzberg, H. Lew, J.J. Sloan, and J.K.G. Watson, Can. J. Phys. 59, 428 (1981). G.Herzberg, J.T. Hougen, and J.K. G. Watson, Can. J. Phys. 60. 1261 (1982)
Dilemmas in educating and improving officers in the field of leadership competences
No full textThere is a need to educate and improve army officers in leadership. Leadership is a factor that increases the likelihood of efficient action and in difficult moments can decide about the results of action. The right choice of goals and content of leadership education, as well as the selection of teachers who have relevant competences are important when designing studies. When choosing the content of education, one should pay attention to the multitude of dilemmas related to leadership. Several of them, discussed in the article, are particularly relevant. They relate to the list of leadership competences that should be shaped, loyalty to subordinates and superiors, the adequacy of the use of forces to the tasks received, the selection of teachers and the phenomenon of captainism. The teacher plays a special role, especially since the process of shaping leadership is a difficult task, which requires acquiring new knowledge, intentional, thought-out didactic activities, and reflection on mistakes and successes.Tomasz Majewski – prof. dr hab., Akademia Sztuki Wojennej w WarszawieDorota Kurek – dr, Akademia Sztuki Wojennej w WarszawieAdair J., Anatomia biznesu. Przywództwo, Studio EMKA, Warszawa 2000.Boguski J., Przywództwo i władza, Ostrołęckie Towarzystwo Naukowe, Ostrołęka 2003.Borkowski M., Dyrda M., Kanarski L., Rokicki B., Człowiek w organizacji, Dom Wydawniczy Elipsa, Warszawa 2001.Bujak A., Nowe wyzwania w akademickim kształceniu nauczycieli, [w:] T. Zacharuk, A. Niewęgłowska (red.), Kompetencje współczesnego nauczyciela, t. 2, Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach, Siedlce 2012.Denek K., Nauczyciel w społeczeństwie wiedzy, jego tożsamość, role, kompetencje i europejski wymiar, [w:] W. Horyń, J. Maciejewski (red.), Nauczyciel andragog we współczesnym społeczeństwie, Wydawnictwo Uniwersytetu Wrocławskiego, Wrocław 2012.Grzybek R., Przewodnik dla lidera. Budowanie zespołu w XXI wieku, MT Biznes, Warszawa 2017.Kaczorowski B. (red.), Leksykon PWN, Warszawa 2004.Kieżun W., Sprawne zarządzanie organizacją, Szkoła Główna Handlowa, Warszawa 1997.Konarzewski K., Nauczyciel, [w:] K. Konarzewski (red.), Sztuka nauczania. Szkoła, Wydawnictwo Naukowe PWN, Warszawa 1993.Majewski T., Kompetencje dowódcze oficerów wojsk lądowych SZ RP, Akademia Obrony Narodowej, Warszawa 2006.Majewski T., Rozwój zawodowy kadr dowódczych w Siłach Zbrojnych, Wydawnictwo Menedżerskie PTM, Warszawa 2013.Rakowska A., Sitko-Lutek A., Doskonalenie kompetencji menedżerskich, Wydawnictwo Naukowe PWN, Warszawa 2000.Robbin S.P., Zachowania w organizacji, Wydawnictwo Zysk i S-ka, Warszawa 1998.Rokicki B., Borkowski J., Kanarski L., Samoocena predyspozycji przywódczych kadry zawodowej, Akademia Obrony Narodowej, Warszawa 2002.Szulc B.M., Przywództwo w dowodzeniu wojskami lądowymi RP. Cz. 1. Koncepcja, AON, Warszawa 2001.Szulc B., Mazurek Z., Majewski T., Wpływ kompetencji kierowniczych, jako wyznacznika profesjonalizmu, na kariery zawodowe oficerów, Akademia Obrony Narodowej, Warszawa 2002.20922
BMC Genomics
No full textCorrection to Bemmo A, Benovoy D, Kwan T, Gaffney DJ, Jensen RV, Majewski J: Gene expression and isoform variation analysis using Affymetrix Exon Arrays. BMC Genomics 2008, 9: 529.Published versio
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