313,118 research outputs found
Formal Development of Rough Inclusion Functions
Rough sets, developed by Pawlak [15], are important tool to describe situation of incomplete or partially unknown information. In this article, continuing the formalization of rough sets [12], we give the formal characterization of three rough inclusion functions (RIFs). We start with the standard one, ÎșÂŁ, connected with Ćukasiewicz [14], and extend this research for two additional RIFs: Îș 1, and Îș 2, following a paper by GomoliĆska [4], [3]. We also define q-RIFs and weak q-RIFs [2]. The paper establishes a formal counterpart of [7] and makes a preliminary step towards rough mereology [16], [17] in Mizar [13].Institute of Informatics, University of BiaĆystok, PolandAnna Gomolinska. A comparative study of some generalized rough approximations. Fundamenta Informaticae, 51:103â119, 2002.Anna Gomolinska. Rough approximation based on weak q-RIFs. In James F. Peters, Andrzej Skowron, Marcin Wolski, Mihir K. Chakraborty, and Wei-Zhi Wu, editors, Transactions on Rough Sets X, volume 5656 of Lecture Notes in Computer Science, pages 117â135, Berlin, Heidelberg, 2009. Springer. ISBN 978-3-642-03281-3. doi:10.1007/978-3-642-03281-3_4.Anna Gomolinska. On three closely related rough inclusion functions. In Marzena Kryszkiewicz, James F. Peters, Henryk Rybinski, and Andrzej Skowron, editors, Rough Sets and Intelligent Systems Paradigms, volume 4585 of Lecture Notes in Computer Science, pages 142â151, Berlin, Heidelberg, 2007. Springer. doi:10.1007/978-3-540-73451-2_16.Anna Gomolinska. On certain rough inclusion functions. In James F. Peters, Andrzej Skowron, and Henryk Rybinski, editors, Transactions on Rough Sets IX, volume 5390 of Lecture Notes in Computer Science, pages 35â55. Springer Berlin Heidelberg, 2008. doi:10.1007/978-3-540-89876-4_3.Adam Grabowski. On the computer-assisted reasoning about rough sets. In B. Dunin-KÄplicz, A. Jankowski, A. Skowron, and M. Szczuka, editors, International Workshop on Monitoring, Security, and Rescue Techniques in Multiagent Systems Location, volume 28 of Advances in Soft Computing, pages 215â226, Berlin, Heidelberg, 2005. Springer-Verlag. doi:10.1007/3-540-32370-8_15.Adam Grabowski. Efficient rough set theory merging. Fundamenta Informaticae, 135(4): 371â385, 2014. doi:10.3233/FI-2014-1129.Adam Grabowski. Building a framework of rough inclusion functions by means of computerized proof assistant. In TamĂĄs MihĂĄlydeĂĄk, Fan Min, Guoyin Wang, Mohua Banerjee, Ivo DĂŒntsch, Zbigniew Suraj, and Davide Ciucci, editors, Rough Sets, volume 11499 of Lecture Notes in Computer Science, pages 225â238, Cham, 2019. Springer International Publishing. ISBN 978-3-030-22815-6. doi:10.1007/978-3-030-22815-6_18.Adam Grabowski. Lattice theory for rough sets â a case study with Mizar. Fundamenta Informaticae, 147(2â3):223â240, 2016. doi:10.3233/FI-2016-1406.Adam Grabowski. Relational formal characterization of rough sets. Formalized Mathematics, 21(1):55â64, 2013. doi:10.2478/forma-2013-0006.Adam Grabowski. Binary relations-based rough sets â an automated approach. Formalized Mathematics, 24(2):143â155, 2016. doi:10.1515/forma-2016-0011.Adam Grabowski and Christoph Schwarzweller. On duplication in mathematical repositories. In Serge Autexier, Jacques Calmet, David Delahaye, Patrick D. F. Ion, Laurence Rideau, Renaud Rioboo, and Alan P. Sexton, editors, Intelligent Computer Mathematics, 10th International Conference, AISC 2010, 17th Symposium, Calculemus 2010, and 9th International Conference, MKM 2010, Paris, France, July 5â10, 2010. Proceedings, volume 6167 of Lecture Notes in Computer Science, pages 300â314. Springer, 2010. doi:10.1007/978-3-642-14128-7_26.Adam Grabowski and MichaĆ Sielwiesiuk. Formalizing two generalized approximation operators. Formalized Mathematics, 26(2):183â191, 2018. doi:10.2478/forma-2018-0016.Adam Grabowski, Artur KorniĆowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191â198, 2015. doi:10.1007/s10817-015-9345-1.Jan Ćukasiewicz. Die logischen Grundlagen der Wahrscheinlichkeitsrechnung. In L. Borkowski, editor, Jan Ćukasiewicz â Selected Works, pages 16â63. North Holland, Polish Scientific Publ., Amsterdam London Warsaw, 1970. First published in KrakĂłw, 1913.ZdzisĆaw Pawlak. Rough sets. International Journal of Parallel Programming, 11:341â356, 1982. doi:10.1007/BF01001956.Lech Polkowski. Rough mereology. In Approximate Reasoning by Parts, volume 20 of Intelligent Systems Reference Library, pages 229â257, Berlin, Heidelberg, 2011. Springer. ISBN 978-3-642-22279-5. doi:10.1007/978-3-642-22279-5_6.Lech Polkowski and Andrzej Skowron. Rough mereology: A new paradigm for approximate reasoning. International Journal of Approximate Reasoning, 15(4):333â365, 1996. doi:10.1016/S0888-613X(96)00072-2.Andrzej Skowron and JarosĆaw Stepaniuk. Tolerance approximation spaces. Fundamenta Informaticae, 27(2/3):245â253, 1996. doi:10.3233/FI-1996-272311.William Zhu. Generalized rough sets based on relations. Information Sciences, 177: 4997â5011, 2007.27433734
Formalizing Two Generalized Approximation Operators
Rough sets, developed by Pawlak [15], are important tool to describe situation of incomplete or partially unknown information. In this article we give the formal characterization of two closely related rough approximations, along the lines proposed in a paper by GomoliĆska [2]. We continue the formalization of rough sets in Mizar [1] started in [6].Adam Grabowski - Institute of Informatics, University of BiaĆystok, PolandMichaĆ Sielwiesiuk - Institute of Informatics, University of BiaĆystok, PolandGrzegorz Bancerek, CzesĆaw ByliĆski, Adam Grabowski, Artur KorniĆowicz, Roman Matuszewski, Adam Naumowicz, Karol PÄ
k, and Josef Urban. Mizar: State-of-the-art and beyond. In Manfred Kerber, Jacques Carette, Cezary Kaliszyk, Florian Rabe, and Volker Sorge, editors, Intelligent Computer Mathematics, volume 9150 of Lecture Notes in Computer Science, pages 261â279. Springer International Publishing, 2015. ISBN 978-3-319-20614-1. doi:10.1007/978-3-319-20615-8_17.Anna GomoliĆska. A comparative study of some generalized rough approximations. Fundamenta Informaticae, 51:103â119, 2002.Adam Grabowski. Automated discovery of properties of rough sets. Fundamenta Informaticae, 128:65â79, 2013. doi:10.3233/FI-2013-933.Adam Grabowski. Lattice theory for rough sets â a case study with Mizar. Fundamenta Informaticae, 147(2â3):223â240, 2016. doi:10.3233/FI-2016-1406.Adam Grabowski. Formalization of generalized almost distributive lattices. Formalized Mathematics, 22(3):257â267, 2014. doi:10.2478/forma-2014-0026.Adam Grabowski. Basic properties of rough sets and rough membership function. Formalized Mathematics, 12(1):21â28, 2004.Adam Grabowski. Relational formal characterization of rough sets. Formalized Mathematics, 21(1):55â64, 2013. doi:10.2478/forma-2013-0006.Adam Grabowski. Binary relations-based rough sets â an automated approach. Formalized Mathematics, 24(2):143â155, 2016. doi:10.1515/forma-2016-0011.Adam Grabowski and Magdalena JastrzÄbska. A note on a formal approach to rough operators. In Marcin S. Szczuka and Marzena Kryszkiewicz et al., editors, Rough Sets and Current Trends in Computing â 7th International Conference, RSCTC 2010, Warsaw, Poland, June 28-30, 2010. Proceedings, volume 6086 of Lecture Notes in Computer Science, pages 307â316. Springer, 2010. doi:10.1007/978-3-642-13529-3_33.Adam Grabowski and Magdalena JastrzÄbska. Rough set theory from a math-assistant perspective. In Rough Sets and Intelligent Systems Paradigms, International Conference, RSEISP 2007, Warsaw, Poland, June 28â30, 2007, Proceedings, pages 152â161, 2007. doi:10.1007/978-3-540-73451-2_17.Adam Grabowski and Christoph Schwarzweller. On duplication in mathematical repositories. In Serge Autexier, Jacques Calmet, David Delahaye, Patrick D. F. Ion, Laurence Rideau, Renaud Rioboo, and Alan P. Sexton, editors, Intelligent Computer Mathematics, 10th International Conference, AISC 2010, 17th Symposium, Calculemus 2010, and 9th International Conference, MKM 2010, Paris, France, July 5â10, 2010. Proceedings, volume 6167 of Lecture Notes in Computer Science, pages 300â314. Springer, 2010. doi:10.1007/978-3-642-14128-7_26.Adam Grabowski and Christoph Schwarzweller. Rough Concept Analysis - theory development in the Mizar system. In Asperti, Andrea and Bancerek, Grzegorz and Trybulec, Andrzej, editor, Mathematical Knowledge Management, Third International Conference, MKM 2004, Bialowieza, Poland, September 19â21, 2004, Proceedings, volume 3119 of Lecture Notes in Computer Science, pages 130â144, 2004. doi:10.1007/978-3-540-27818-4_10. 3rd International Conference on Mathematical Knowledge Management, Bialowieza, Poland, Sep. 19-21, 2004.Jouni JĂ€rvinen. Lattice theory for rough sets. Transactions of Rough Sets, VI, Lecture Notes in Computer Science, 4374:400â498, 2007.Eliza Niewiadomska and Adam Grabowski. Introduction to formal preference spaces. Formalized Mathematics, 21(3):223â233, 2013. doi:10.2478/forma-2013-0024.ZdzisĆaw Pawlak. Rough sets. International Journal of Parallel Programming, 11:341â356, 1982. doi:10.1007/BF01001956.Y.Y. Yao. Two views of the theory of rough sets in finite universes. International Journal of Approximate Reasoning, 15(4):291â317, 1996. doi:10.1016/S0888-613X(96)00071-0.William Zhu. Generalized rough sets based on relations. Information Sciences, 177: 4997â5011, 2007.26218319
Partial Correctness of a Power Algorithm
This work continues a formal verification of algorithms written in terms of simple-named complex-valued nominative data [6],[8],[15],[11],[12],[13]. In this paper we present a formalization in the Mizar system [3],[1] of the partial correctness of the algorithm: i := val.1 j := val.2 b := val.3 n := val.4 s := val.5 while (i n) i := i + j s := s * b return s computing the natural n power of given complex number b, where variables i, b, n, s are located as values of a V-valued Function, loc, as: loc/.1 = i, loc/.3 = b, loc/.4 = n and loc/.5 = s, and the constant 1 is located in the location loc/.2 = j (set V represents simple names of considered nominative data [17]).The validity of the algorithm is presented in terms of semantic Floyd-Hoare triples over such data [9]. Proofs of the correctness are based on an inference system for an extended Floyd-Hoare logic [2],[4] with partial pre- and post-conditions [14],[16],[7],[5].Institute of Informatics, University of BiaĆystok, PolandGrzegorz Bancerek, CzesĆaw ByliĆski, Adam Grabowski, Artur KorniĆowicz, Roman Matuszewski, Adam Naumowicz, and Karol PÄ
k. The role of the Mizar Mathematical Library for interactive proof development in Mizar. Journal of Automated Reasoning, 61(1):9â32, 2018. doi:10.1007/s10817-017-9440-6.R.W. Floyd. Assigning meanings to programs. Mathematical aspects of computer science, 19(19â32), 1967.Adam Grabowski, Artur KorniĆowicz, and Adam Naumowicz. Four decades of Mizar. Journal of Automated Reasoning, 55(3):191â198, 2015. doi:10.1007/s10817-015-9345-1.C.A.R. Hoare. An axiomatic basis for computer programming. Commun. ACM, 12(10): 576â580, 1969.Ievgen Ivanov and Mykola Nikitchenko. On the sequence rule for the Floyd-Hoare logic with partial pre- and post-conditions. In Proceedings of the 14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, Kyiv, Ukraine, May 14â17, 2018, volume 2104 of CEUR Workshop Proceedings, pages 716â724, 2018.Ievgen Ivanov, Mykola Nikitchenko, Andrii Kryvolap, and Artur KorniĆowicz. Simple-named complex-valued nominative data â definition and basic operations. Formalized Mathematics, 25(3):205â216, 2017. doi:10.1515/forma-2017-0020.Ievgen Ivanov, Artur KorniĆowicz, and Mykola Nikitchenko. Implementation of the composition-nominative approach to program formalization in Mizar. The Computer Science Journal of Moldova, 26(1):59â76, 2018.Ievgen Ivanov, Artur KorniĆowicz, and Mykola Nikitchenko. On an algorithmic algebra over simple-named complex-valued nominative data. Formalized Mathematics, 26(2):149â158, 2018. doi:10.2478/forma-2018-0012.Ievgen Ivanov, Artur KorniĆowicz, and Mykola Nikitchenko. An inference system of an extension of Floyd-Hoare logic for partial predicates. Formalized Mathematics, 26(2): 159â164, 2018. doi:10.2478/forma-2018-0013.Ievgen Ivanov, Artur KorniĆowicz, and Mykola Nikitchenko. Partial correctness of GCD algorithm. Formalized Mathematics, 26(2):165â173, 2018. doi:10.2478/forma-2018-0014.Ievgen Ivanov, Artur KorniĆowicz, and Mykola Nikitchenko. On algebras of algorithms and specifications over uninterpreted data. Formalized Mathematics, 26(2):141â147, 2018. doi:10.2478/forma-2018-0011.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the algebra of nominative data in Mizar. In Maria Ganzha, Leszek A. Maciaszek, and Marcin Paprzycki, editors, Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, FedCSIS 2017, Prague, Czech Republic, September 3â6, 2017., pages 237â244, 2017. ISBN 978-83-946253-7-5. doi:10.15439/2017F301.Artur Kornilowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. Formalization of the nominative algorithmic algebra in Mizar. In Leszek Borzemski, Jerzy ĆwiÄ
tek, and Zofia Wilimowska, editors, Information Systems Architecture and Technology: Proceedings of 38th International Conference on Information Systems Architecture and Technology â ISAT 2017 â Part II, Szklarska PorÄba, Poland, September 17â19, 2017, volume 656 of Advances in Intelligent Systems and Computing, pages 176â186. Springer, 2017. ISBN 978-3-319-67228-1. doi:10.1007/978-3-319-67229-8_16.Artur KorniĆowicz, Andrii Kryvolap, Mykola Nikitchenko, and Ievgen Ivanov. An approach to formalization of an extension of Floyd-Hoare logic. In Vadim Ermolayev, Nick Bassiliades, Hans-Georg Fill, Vitaliy Yakovyna, Heinrich C. Mayr, Vyacheslav Kharchenko, Vladimir Peschanenko, Mariya Shyshkina, Mykola Nikitchenko, and Aleksander Spivakovsky, editors, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer, Kyiv, Ukraine, May 15â18, 2017, volume 1844 of CEUR Workshop Proceedings, pages 504â523. CEUR-WS.org, 2017.Artur KorniĆowicz, Ievgen Ivanov, and Mykola Nikitchenko. Kleene algebra of partial predicates. Formalized Mathematics, 26(1):11â20, 2018. doi:10.2478/forma-2018-0002.Andrii Kryvolap, Mykola Nikitchenko, and Wolfgang Schreiner. Extending Floyd-Hoare logic for partial pre- and postconditions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications: 9th International Conference, ICTERI 2013, Kherson, Ukraine, June 19â22, 2013, Revised Selected Papers, pages 355â378. Springer International Publishing, 2013. ISBN 978-3-319-03998-5. doi:10.1007/978-3-319-03998-5_18.Volodymyr G. Skobelev, Mykola Nikitchenko, and Ievgen Ivanov. On algebraic properties of nominative data and functions. In Vadim Ermolayev, Heinrich C. Mayr, Mykola Nikitchenko, Aleksander Spivakovsky, and Grygoriy Zholtkevych, editors, Information and Communication Technologies in Education, Research, and Industrial Applications â 10th International Conference, ICTERI 2014, Kherson, Ukraine, June 9â12, 2014, Revised Selected Papers, volume 469 of Communications in Computer and Information Science, pages 117â138. Springer, 2014. ISBN 978-3-319-13205-1. doi:10.1007/978-3-319-13206-8_6.27218919
Intelligent Integrated Management for Telecommunication Networks
As the size of communication networks keeps on growing, faster connections, cooperating technologies and the divergence of equipment and data communications, the management of the resulting networks gets additional important and time-critical. More advanced tools are needed to support this activity. In this article we describe the design and implementation of a management platform using Artificial Intelligent reasoning technique. For this goal we make use of an expert system. This study focuses on an intelligent framework and a language for formalizing knowledge management descriptions and combining them with existing OSI management model. We propose a new paradigm where the intelligent network management is integrated into the conceptual repository of management information called Managed Information Base (MIB). This paper outlines the development of an expert system prototype based in our propose GDMO+ standard and describes the most important facets, advantages and drawbacks that were found after prototyping our proposal
Intelligent Packaging Systems: Sensors and Nanosensors to Monitor Food Quality and Safety
IndexaciĂłn: Web of Science y Scopus.The application of nanotechnology in different areas of food packaging is an emerging field that will grow rapidly in the coming years. Advances in food safety have yielded promising results leading to the development of intelligent packaging (IP). By these containers, it is possible to monitor and provide information of the condition of food, packaging, or the environment. This article describes the role of the different concepts of intelligent packaging. It is possible that this new technology could reach enhancing food safety, improving pathogen detection time, and controlling the quality of food and packaging throughout the supply chain.https://www.hindawi.com/journals/js/2016/4046061/cta
An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders
The data mining along with emerging computing techniques have astonishingly
influenced the healthcare industry. Researchers have used different Data Mining
and Internet of Things (IoT) for enrooting a programmed solution for diabetes
and heart patients. However, still, more advanced and united solution is needed
that can offer a therapeutic opinion to individual diabetic and cardio
patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced
healthcare system for proficient diabetes and cardiovascular diseases have been
proposed. The hybridization of data mining and IoT with other emerging
computing techniques is supposed to give an effective and economical solution
to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining,
Internet of Things, chatbots, contextual entity search (CES), bio-sensors,
semantic analysis and granular computing (GC). The bio-sensors of the proposed
system assist in getting the current and precise status of the concerned
patients so that in case of an emergency, the needful medical assistance can be
provided. The novelty lies in the hybrid framework and the adequate support of
chatbots, granular computing, context entity search and semantic analysis. The
practical implementation of this system is very challenging and costly.
However, it appears to be more operative and economical solution for diabetes
and cardio patients.Comment: 11 PAGE
Scheduling of non-repetitive lean manufacturing systems under uncertainty using intelligent agent simulation
World-class manufacturing paradigms emerge from specific types of manufacturing systems with which they remain associated until they are obsolete. Since its introduction the lean paradigm is almost exclusively implemented in repetitive manufacturing systems employing flow-shop layout configurations. Due to its inherent complexity and combinatorial nature, scheduling is one application domain whereby the implementation of manufacturing philosophies and best practices is particularly challenging. The study of the limited reported attempts to extend leanness into the scheduling of non-repetitive manufacturing systems with functional shop-floor configurations confirms that these works have adopted a similar approach which aims to transform the system mainly through reconfiguration in order to increase the degree of manufacturing repetitiveness and thus facilitate the adoption of leanness. This research proposes the use of leading edge intelligent agent simulation to extend the lean principles and techniques to the scheduling of non-repetitive production environments with functional layouts and no prior reconfiguration of any form. The simulated system is a dynamic job-shop with stochastic order arrivals and processing times operating under a variety of dispatching rules. The modelled job-shop is subject to uncertainty expressed in the form of high priority orders unexpectedly arriving at the system, order cancellations and machine breakdowns. The effect of the various forms of the stochastic disruptions considered in this study on system performance prior and post the introduction of leanness is analysed in terms of a number of time, due date and work-in-progress related performance metrics
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