425,633 research outputs found

    Formal Introduction to Fuzzy Implications

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    SummaryIn the article we present in the Mizar system the catalogue of nine basic fuzzy implications, used especially in the theory of fuzzy sets. This work is a continuation of the development of fuzzy sets in Mizar; it could be used to give a variety of more general operations, and also it could be a good starting point towards the formalization of fuzzy logic (together with t-norms and t-conorms, formalized previously).Institute of Informatics, University of Białystok, PolandMichał Baczyński and Balasubramaniam Jayaram. Fuzzy Implications. Springer Publishing Company, Incorporated, 2008. doi:10.1007/978-3-540-69082-5.Adam Grabowski. Basic formal properties of triangular norms and conorms. Formalized Mathematics, 25(2):93–100, 2017. doi:10.1515/forma-2017-0009.Adam Grabowski. The formal construction of fuzzy numbers. Formalized Mathematics, 22(4):321–327, 2014. doi:10.2478/forma-2014-0032.Adam Grabowski. On the computer certification of fuzzy numbers. In M. Ganzha, L. Maciaszek, and M. Paprzycki, editors, 2013 Federated Conference on Computer Science and Information Systems (FedCSIS), Federated Conference on Computer Science and Information Systems, pages 51–54, 2013.Adam Grabowski. Lattice theory for rough sets – a case study with Mizar. Fundamenta Informaticae, 147(2–3):223–240, 2016. doi:10.3233/FI-2016-1406.Adam Grabowski and Magdalena Jastrzębska. Rough set theory from a math-assistant perspective. In Rough Sets and Intelligent Systems Paradigms, International Conference, RSEISP 2007, Warsaw, Poland, June 28–30, 2007, Proceedings, pages 152–161, 2007. doi:10.1007/978-3-540-73451-2_17.Adam Grabowski and Takashi Mitsuishi. Extending Formal Fuzzy Sets with Triangular Norms and Conorms, volume 642: Advances in Intelligent Systems and Computing, pages 176–187. Springer International Publishing, Cham, 2018. doi:10.1007/978-3-319-66824-6_16.Adam Grabowski and Takashi Mitsuishi. Initial comparison of formal approaches to fuzzy and rough sets. In Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, and Jacek M. Zurada, editors, Artificial Intelligence and Soft Computing - 14th International Conference, ICAISC 2015, Zakopane, Poland, June 14-18, 2015, Proceedings, Part I, volume 9119 of Lecture Notes in Computer Science, pages 160–171. Springer, 2015. doi:10.1007/978-3-319-19324-3_15.Adam Grabowski, Artur Korniłowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191–198, 2015. doi:10.1007/s10817-015-9345-1.Takashi Mitsuishi, Noboru Endou, and Yasunari Shidama. The concept of fuzzy set and membership function and basic properties of fuzzy set operation. Formalized Mathematics, 9(2):351–356, 2001.Zdzisław Pawlak. Rough sets. International Journal of Parallel Programming, 11:341–356, 1982. doi:10.1007/BF01001956.Lotfi Zadeh. Fuzzy sets. Information and Control, 8(3):338–353, 1965.25324124

    Aligning operational and corporate goals: a case study in cultivating a whole-of-business approach using a supply chain simulation game

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    This paper outlines the development and use of an interactive computer-based supply chain game to facilitate the alignment of disconnected operational and corporate goals. A multi-enterprise internal cattle supply chain was simulated targeting the operational property managers and the overall impacts of their decision making on corporate goals A three stage multidisciplinary approach was used. A case study based financial analysis was undertaken across the internal cattle supply chain, a participative action research component (developing the game to simulate the flow of product and associated decisions and financial transactions through the internal supply chain of the company for different operational scenarios using measurable and familiar operational and financial criteria as tracking tools), and a qualitative analysis of organisational learning through player debriefing following playing the game. Evaluation of the managers' learning around the need for a change in general practice to address goal incongruence was positive evidenced by changes in practice and the game regarded by the users as a useful form of organisational training. The game provided property managers with practical insights into the strategic implications of their enterprise level decisions on the internal supply chain and on overall corporate performance. The game is unique and is a tool that can be used to help address an endemic problem across multi-enterprise industries in the agrifood sector in Australia

    The role of sex differences in detecting deception in computer-mediated communication in English

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    [EN] While deception seems to be a common approach in interpersonal communication, most examination on interpersonal deception sees the sex of the interlocutor as unconnected with the capability to notice deceptive messages. This research studies the truth and deception detection capability of both male and female receivers when replying to both true and deceptive messages from both male and female speakers. The outcomes indicate that sex may be a significant variable in comprehending the interpersonal detection probabilities of truth and of lies. An interaction of variables including the speakers’ sex, receivers’ sex, and whether the message appears to be truthful or deceptive is created to relate to detection capability.Kuzio, A. (2018). The role of sex differences in detecting deception in computer-mediated communication in English. Journal of Computer-Assisted Linguistic Research. 2(1):39-53. doi:10.4995/jclr.2018.10521SWORD395321Aamodt, M. G., & Custer, H. (2006). Who can best catch a liar? A meta-analysis of individual differences in detecting deception. The Forensic Examiner, 15(1), 6-11.Blalock, H. M. (1972). Social Statistics. New York: McGraw Hill.Bond, C. F., & DePaulo, B. M. (2006). Accuracy of deception judgments. Personality and Social Psychology Review, 10(3), 214-234. https://doi.org/10.1207/s15327957pspr1003_2Boush, D. M., Friestad, M., & Wright, P. (2009). Deception in the marketplace : The psychology of deceptive persuasion and consumer self-protection. New York: Routledge.Camden, C., Motley, M. T., & Wilson, A. (1984). White lies in interpersonal communication: A taxonomy and preliminary investigation of social motivations. Western Journal of Speech Communication, 48(4), 309-325. https://doi.org/10.1080/10570318409374167Carlson, J., George, J., Burgoon, J., Adkins, M., & White, C. (2004). Deception in computer mediated communication. Group Decision and Negotiation, 13, 5-28. https://doi.org/10.1023/B:GRUP.0000011942.31158.d8Daft, R.L. & Lengel, R.H. (1986). Information richness: A new approach to managerial behavior and organizational design. In Cummings, L. L. & Staw, B.M. (Eds.), Research in organizational behavior 6 (pp. 191-233). Homewood, IL: JAI Press.DePaulo, B. M., Epstein, J. A., & Wyer, M. M. (1993). Sex differences in lying: How women and men deal with the dilemma of deceit. In M. Lewis, & C. Saarni (Eds.), Lying and deception in everyday life (pp. 126-147). New York: Guilford Press.DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., Wyer, M. M., & Epstein, J. A. (1996). Lying in everyday life. Journal of Personality and Social Psychology, 70(5), 979- 995. https://doi.org/10.1037/0022-3514.70.5.979DePaulo, B. M., Kirkendol, S. E., Tang, J., & O'Brien, T. P. (1988). The motivational impairment effect in the communication of deception: Replications and extensions. Journal of Nonverbal Behavior, 12(3), 177-202. https://doi.org/10.1007/BF00987487DePaulo, B. M., Lassiter, G. D., & Stone, J. L. (1982). Attention all determinants of success at detecting deception and truth. Personality and Social Psychology Bulletin, 8(2), 273-279. https://doi.org/10.1177/0146167282082014DePaulo, B. M., & Rosenthal, R. (1981). Telling lies. Journal of Personality and Social Psychology, 37(10), 1713-1722. https://doi.org/10.1037/0022-3514.37.10.1713Dreber, A., & Johannesson, M. (2008). Gender differences in deception. Economics Letters, 99(1), 197-199. https://doi.org/10.1016/j.econlet.2007.06.027Ekman, P., & O'Sullivan, M. (1991). Who can catch a liar? American Psychologist, 46(9), 913-920. https://doi.org/10.1037/0003-066X.46.9.913Ekman, P., O'Sullivan, M., & Frank, M. G. (1999). A few can catch a liar. Psychological Science, 10(3), 263-266. https://doi.org/10.1111/1467-9280.00147Feldman, R. S., Forrest, J. A., & Happ, B. R. (2002). Self-presentation and verbal deception: Do self-presenters lie more? Basic and Applied Social Psychology, 24(2), 163-170. https://doi.org/10.1207/153248302753674848George, J. F., & Robb, A. (2008). Deception and computer-mediated communication in daily life. Communication Reports, 21(2), 92-103. https://doi.org/10.1080/08934210802298108Hample, D. (1980). Purposes and effects of lying. Southern Speech Communication Journal, 46(1), 33-47. https://doi.org/10.1080/10417948009372474Hancock, J., Thom-Santelli, J., & Ritchie, T. (2004). Deception and design: The impact of communication technology on lying behavior. In E. Dykstra-Erickson, & M. Tscheligi (Eds.), Proceedings of the 2004 conference on human factors in computing systems (pp. 129-134). New York: Association for Computing Machinery.https://doi.org/10.1145/985692.985709Haselton, M. G., Buss, D. M., Oubaid, V., & Angleitner, A. (2005). Sex, lies, and strategic interference: The psychology of deception between the sexes. Personality and Social Psychology Bulletin, 31(1), 3-23. https://doi.org/10.1177/0146167204271303Inglehart, R., Basa-ez, M., & Moreno, A. (1998). Human values and beliefs: A crosscultural sourcebook. Ann Arbor, MI: University of Michigan Press. https://doi.org/10.3998/mpub.14858Knapp, L. M., Hart, R. P., & Dennis, H. S. (1974). An exploration of deception as a communication construct. Human Communication Research, 1(1), 15-29. https://doi.org/10.1111/j.1468-2958.1974.tb00250.xKraut, R. E. (1980). Behavioral roots of person perception: The deception judgments of customs inspectors and laymen. Journal of Personality and Social Psychology, 39(5), 784-798. https://doi.org/10.1037/0022-3514.39.5.784Kuzio, A. (2018). Cross-cultural Deception in Polish and American English in Computer-Mediated Communication. New Castle upon Tyne: Cambridge Scholars Publishing.Levine, T. R., & Kim, R. K. (2010). Some considerations for a new theory of deceptive communication. In M. S. McGlone, & M. L. Knapp (Eds.), The interplay of truth and deception: New agendas in theory and research (pp. 16-34). New York: Routledge.Levine, T. R., Park, H. S., & McCornack, S. A. (2006). Accuracy in detecting truths and lies: Documenting the "Veracity Effect". Communication Monographs, 66(2), 125- 144. https://doi.org/10.1080/03637759909376468Manstead, A., Wagner, H. L., & McDonald, C. J. (1986). Deceptive and non-deceptive communications: Sending experience, modality, and individual abilities. Journal of Nonverbal Behavior, 10(3), 147-167. https://doi.org/10.1007/BF00987612McCornack, S. A., & Parks, M. R. (1990). What women know that men don't: Sex differences in determining the truth behind deceptive messages. Journal of Social and Personal Relationships, 7(1), 107-118. https://doi.org/10.1177/0265407590071006Park, H. S., Levine, T. R., McCornack, S. A., Morrison, K., & Ferrara, M. (2002). How people really detect lies. Communication Monographs, 69(2), 144-157. https://doi.org/10.1080/714041710Prater, T., & Kiser, S. B. (2002). Lies, lies, and more lies. SAM Advanced Management Journal,67(2), 9-36.Sanchez-Pages, S., & Vorsatz, M. (2008). Enjoy the silence: An experiment on truthtelling. Experimental Economics, 12(2), 220-241. https://doi.org/10.1007/s10683-008-9211-7Seiter, J. S., Bruschke, J., & Bai, C. (2002). The acceptability of deception as a function of perceivers' culture, deceiver's intention, and deceiver-deceived relationship. Western Journal of Communication, 66(2), 158-180. https://doi.org/10.1080/10570310209374731Serota, K. B., Levine, T. R., & Boster, F. J. (2010). The prevalence of lying in America: Three studies of self-reported lies. Human Communication Research, 36(1), 2-25. https://doi.org/10.1111/j.1468-2958.2009.01366.xTurner, R. E., Edgley, C., & Olmstead, G. (1975). Information control in conversations: Honesty is not always the best policy. Kansas Journal of Sociology, 11(1), 69-89.https://doi.org/10.17161/STR.1808.6098Zuckerman, M., DePaulo, B. M., & Rosenthal, R. (1981). Verbal and nonverbal communication of deception. In L. Berkowitz (Ed.), Advances in experimental social psychology (volume 11, pp. 1-59). New York: Academic Press.https://doi.org/10.1016/S0065-2601(08)60369-

    Factors Influencing People’s Intention to Adopt E-Banking: An Empirical Study of Consumers in Shandong Province, China

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    E-Banking is growing at an unprecedented rate and has become a truly worldwide phenomenon, offering convenience, flexibility and interactivity for those that can, and know how to access it. This is clearly evidence in China. However, despite such growth and popularity, some users still have reservations about using Information and communication technology (ICT) in their daily banking activities, perhaps due to deep routed cultural factors that cause consumers to question the efficacy of such changes. Through the application of a technology acceptance framework, and empirical evidence from 52 E-Banking user questionnaires and four key market segment interviews, the research explores the factors that influence consumers’ intention to adopt E-Banking in Shandong Province of China. The findings highlight that perceived usefulness and perceived credibility are significant factors which have a positive influence on consumers’ intention to utilise E-Banking, while perceived ease of use and perceived cost are less significant. Unpacking the reasons for resistance to the use of E-Banking highlighted that “difficult to operate”, “unnecessary to use it” and “worry about the security” are key drivers and therefore challenges for the service providers. Based on the results, recommendations are drawn for banks, involving focusing on the significant factors, avoiding weaknesses and optimising strengths of E-Banking and ultimately developing more accurate market positioning strategies to align and manage consumer expectations and maximise potential acceptance

    Computer Abuse: The Emerging Crime and the Need for Legislation

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    Advancements in computerization and the growing use of computers in business, government, education, and the private sector has resulted in the expanding potential for criminal infiltration. The problems of computer crime are in great part attributable to the shortcomings of our criminal laws, which were written long before there was knowledge of computer crimes. Moreover, there is a reluctance of our legal establishments to adapt to the new technology\u27s potential harm. This Note urges that new federal legislation be passed as a means to counteract future computer crimes

    Caged calcium in Aplysia pacemaker neurons. Characterization of calcium-activated potassium and nonspecific cation currents.

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    We have studied calcium-activated potassium current, IK(Ca), and calcium-activated nonspecific cation current, INS(Ca), in Aplysia bursting pacemaker neurons, using photolysis of a calcium chelator (nitr-5 or nitr-7) to release caged calcium intracellularly. A computer model of nitr photolysis, multiple buffer equilibration, and active calcium extrusion was developed to predict volume-average and front-surface calcium concentration transients. Changes in arsenazo III absorbance were used to measure calcium concentration changes caused by nitr photolysis in microcuvettes. Our model predicted the calcium increments caused by successive flashes, and their dependence on calcium loading, nitr concentration, and light intensity. Flashes also triggered the predicted calcium concentration jumps in neurons filled with nitr-arsenazo III mixtures. In physiological experiments, calcium-activated currents were recorded under voltage clamp in response to flashes of different intensity. Both IK(Ca) and INS(Ca) depended linearly without saturation upon calcium concentration jumps of 0.1-20 microM. Peak membrane currents in neurons exposed to repeated flashes first increased and then declined much like the arsenazo III absorbance changes in vitro, which also indicates a first-order calcium activation. Each flash-evoked current rose rapidly to a peak and decayed to half in 3-12 s. Our model mimicked this behavior when it included diffusion of calcium and nitr perpendicular to the surface of the neuron facing the flashlamp. Na/Ca exchange extruding about 1 pmol of calcium per square centimeter per second per micromolar free calcium appeared to speed the decline of calcium-activated membrane currents. Over a range of different membrane potentials, IK(Ca) and INS(Ca) decayed at similar rates, indicating similar calcium stoichiometries independent of voltage. IK(Ca), but not INS(Ca), relaxes exponentially to a different level when the voltage is suddenly changed. We have estimated voltage-dependent rate constants for a one-step first-order reaction scheme of the activation of IK(Ca) by calcium. After a depolarizing pulse, INS(Ca) decays at a rate that is well predicted by a model of diffusion of calcium away from the inner membrane surface after it has entered the cell, with active extrusion by surface pumps and uptake into organelles. IK(Ca) decays somewhat faster than INS(Ca) after a depolarization, because of its voltage-dependent relaxation combined with the decay of submembrane calcium. The interplay of these two currents accounts for the calcium-dependent outward-inward tail current sequence after a depolarization, and the corresponding afterpotentials after a burs

    Generating indicative-informative summaries with SumUM

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    We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies
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