Cinnamons: A Computation Model Underlying Control Network Programming

We give the easily recognizable name "cinnamon" and "cinnamon programming" to a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming paradigm combining declarative and imperative features, built-in search engine, powerful tools for search control that allow easy, intuitive, visual development of heuristic, nondeterministic, and randomized solutions. We define rigorously the syntax and semantics of the new model of computation, at the same time trying to keep clear the intuition behind and to include enough examples. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing-completeness), and the "real" CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming into the directions of nondeterminism, randomness, and fuzziness.Comment: 7th Intl Conf. on Computer Science, Engineering & Applications (ICCSEA 2017) September 23~24, 2017, Copenhagen, Denmar

Developmental Flight Test of a Powered Approach Stability Augmentation System on the U.S. Navy\u27s E- 2C Hawkeye 2000 Aircraft

The E-2C aircraft is a Navy carrier based high-wing, twin engine turboprop powered aircraft used for the Airborne Early Warning (AEW) mission. In the power approach configuration, the aircraft displays strong adverse yaw, weak directional stability, and excessive rudder control power. These antagonistic characteristics, when coupled together, result in an extremely high workload for the pilot during both carrier and field landings. Although the aircraft has a yaw axis stability augmentation system, it is currently only applicable to cruise conditions. Engaging the stability augmentation in the power approach configuration results in a 1 Hz directional oscillation due to the system’s high gain schedule. Additionally, another attribute of the existing system design results in extremely high rudder pedal forces while maintaining sideslip in crosswind conditions. Northrop Grumman developed Flight Control Computer (FCC) software patches designed to improve the handling qualities on landing approaches. These patches are designed to change the rudder control gain schedule to allow the use of stability augmentation in the power approach configuration and suppress the divergent Phugoid characteristic throughout the flight envelope. The system is a directional axis controller only and termed the Powered Approach Stability Augmentation System (PASAS). Initial flight tests on a developmental system provided the design parameters for the production system, which was eventually installed in the Navy’s newest E-2C variant, termed Hawkeye 2000. The ensuing flight test program consisted of land based test flights during the summer of 2001, and culminated in a ship trial consisting of multiple landings on the USS Truman in March of 2002

Relative-fuzzy: a novel approach for handling complex ambiguity for software engineering of data mining models

There are two main defined classes of uncertainty namely: fuzziness and ambiguity, where ambiguity is ‘one-to-many’ relationship between syntax and semantic of a proposition. This definition seems that it ignores ‘many-to-many’ relationship ambiguity type of uncertainty. In this thesis, we shall use complex-uncertainty to term many-to-many relationship ambiguity type of uncertainty. This research proposes a new approach for handling the complex ambiguity type of uncertainty that may exist in data, for software engineering of predictive Data Mining (DM) classification models. The proposed approach is based on Relative-Fuzzy Logic (RFL), a novel type of fuzzy logic. RFL defines a new formulation of the problem of ambiguity type of uncertainty in terms of States Of Proposition (SOP). RFL describes its membership (semantic) value by using the new definition of Domain of Proposition (DOP), which is based on the relativity principle as defined by possible-worlds logic. To achieve the goal of proposing RFL, a question is needed to be answered, which is: how these two approaches; i.e. fuzzy logic and possible-world, can be mixed to produce a new membership value set (and later logic) that able to handle fuzziness and multiple viewpoints at the same time? Achieving such goal comes via providing possible world logic the ability to quantifying multiple viewpoints and also model fuzziness in each of these multiple viewpoints and expressing that in a new set of membership value. Furthermore, a new architecture of Hierarchical Neural Network (HNN) called ML/RFL-Based Net has been developed in this research, along with a new learning algorithm and new recalling algorithm. The architecture, learning algorithm and recalling algorithm of ML/RFL-Based Net follow the principles of RFL. This new type of HNN is considered to be a RFL computation machine. The ability of the Relative Fuzzy-based DM prediction model to tackle the problem of complex ambiguity type of uncertainty has been tested. Special-purpose Integrated Development Environment (IDE) software, which generates a DM prediction model for speech recognition, has been developed in this research too, which is called RFL4ASR. This special purpose IDE is an extension of the definition of the traditional IDE. Using multiple sets of TIMIT speech data, the prediction model of type ML/RFL-Based Net has classification accuracy of 69.2308%. This accuracy is higher than the best achievements of WEKA data mining machines given the same speech data

A neuro-collision avoidance strategy for robot manipulators

The area of collision avoidance and path planning in robotics has received much attention in the research community. Our study centers on a combination of an artificial neural network paradigm with a motion planning strategy that insures safe motion of the Articulated Two-Link Arm with Scissor Hand System relative to an object. Whenever an obstacle is encountered, the arm attempts to slide along the obstacle surface, thereby avoiding collision by means of the local tangent strategy and its artificial neural network implementation. This combination compensates the inverse kinematics of a robot manipulator. Simulation results indicate that a neuro-collision avoidance strategy can be achieved by means of a learning local tangent method

Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process

[EN] This paper addresses one of the most common problems that a railway infrastructure manager has to face: to prioritise a portfolio of maintenance, renewal and improvement (MR&I) projects in a railway network. This decision-making problem is complex due to the large number of MR&I projects in the portfolio and the different criteria to take into consideration, most of which are influenced and interrelated to each other. To address this problem, the use of the analytic network process (ANP) is proposed. The method is applied to a case study in which the Local Manager of the public company, who is responsible for the MR&I of Spanish Rail Lines, has to select the MR&I projects which have to be executed first. Based on the results, it becomes evident that, for this case study, the main factor of preference for a project is the location of application rather than the type of project. The main contributions of this work are: the deep analysis done to identify and weigh the decision criteria, how to assess the alternatives and provide a rigorous and systematic decision-making process, based on an exhaustive revision of the literature and expertiseThe translation of this paper was funded by the Universitat Politecnica de Valencia.Montesinos-Valera, J.; Aragonés-Beltrán, P.; Pastor-Ferrando, J. (2017). Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process. Structure and Infrastructure Engineering. 13(11):1476-1496. https://doi.org/10.1080/15732479.2017.1294189S147614961311Abril, M., Barber, F., Ingolotti, L., Salido, M. A., Tormos, P., & Lova, A. (2008). An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review, 44(5), 774-806. doi:10.1016/j.tre.2007.04.001Ahern, A., & Anandarajah, G. (2007). Railway projects prioritisation for investment: Application of goal programming. Transport Policy, 14(1), 70-80. doi:10.1016/j.tranpol.2006.10.003Al-Harbi, K. M. A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19-27. doi:10.1016/s0263-7863(99)00038-1Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J. P., & Rodríguez-Pozo, F. (2010). An ANP-based approach for the selection of photovoltaic solar power plant investment projects. Renewable and Sustainable Energy Reviews, 14(1), 249-264. doi:10.1016/j.rser.2009.07.012Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J.-P., & Pla-Rubio, A. (2014). An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy, 66, 222-238. doi:10.1016/j.energy.2013.12.016Arif, F., Bayraktar, M. E., & Chowdhury, A. G. (2016). Decision Support Framework for Infrastructure Maintenance Investment Decision Making. Journal of Management in Engineering, 32(1), 04015030. doi:10.1061/(asce)me.1943-5479.0000372Arunraj, N. S., & Maiti, J. (2010). Risk-based maintenance policy selection using AHP and goal programming. Safety Science, 48(2), 238-247. doi:10.1016/j.ssci.2009.09.005Asensio, J., & Matas, A. (2008). Commuters’ valuation of travel time variability. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1074-1085. doi:10.1016/j.tre.2007.12.002Bana e Costa, C. A., & Oliveira, R. C. (2002). Assigning priorities for maintenance, repair and refurbishment in managing a municipal housing stock. European Journal of Operational Research, 138(2), 380-391. doi:10.1016/s0377-2217(01)00253-3Bana e Costa, C. A., & Vansnick, J.-C. (2008). A critical analysis of the eigenvalue method used to derive priorities in AHP. 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European Journal of Operational Research, 24(2), 228-238. doi:10.1016/0377-2217(86)90044-5Cantarelli, C. C., van Wee, B., Molin, E. J. E., & Flyvbjerg, B. (2012). Different cost performance: different determinants? Transport Policy, 22, 88-95. doi:10.1016/j.tranpol.2012.04.002Cheng, C.-H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research, 96(2), 343-350. doi:10.1016/s0377-2217(96)00026-4Cheng, E. W. L., & Li, H. (2005). Analytic Network Process Applied to Project Selection. Journal of Construction Engineering and Management, 131(4), 459-466. doi:10.1061/(asce)0733-9364(2005)131:4(459)Damart, S., & Roy, B. (2009). The uses of cost–benefit analysis in public transportation decision-making in France. Transport Policy, 16(4), 200-212. doi:10.1016/j.tranpol.2009.06.002Durango-Cohen, P. L., & Madanat, S. M. (2008). Optimization of inspection and maintenance decisions for infrastructure facilities under performance model uncertainty: A quasi-Bayes approach. Transportation Research Part A: Policy and Practice, 42(8), 1074-1085. doi:10.1016/j.tra.2008.03.004Durango-Cohen, P. L., & Sarutipand, P. (2009). Maintenance optimization for transportation systems with demand responsiveness. Transportation Research Part C: Emerging Technologies, 17(4), 337-348. doi:10.1016/j.trc.2009.01.001Dyer, J. S. (1990). Remarks on the Analytic Hierarchy Process. Management Science, 36(3), 249-258. doi:10.1287/mnsc.36.3.249Famurewa, S. M., Asplund, M., Rantatalo, M., Parida, A., & Kumar, U. (2014). Maintenance analysis for continuous improvement of railway infrastructure performance. Structure and Infrastructure Engineering, 11(7), 957-969. doi:10.1080/15732479.2014.921929Famurewa, S. M., Stenström, C., Asplund, M., Galar, D., & Kumar, U. (2014). Composite indicator for railway infrastructure management. Journal of Modern Transportation, 22(4), 214-224. doi:10.1007/s40534-014-0051-1Figueira, J., Greco, S., & Ehrogott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science. doi:10.1007/b100605FitzRoy, F., & Smith, I. (1995). The demand for rail transport in European countries. Transport Policy, 2(3), 153-158. doi:10.1016/0967-070x(95)96745-7Furuya, A., & Madanat, S. (2013). Accounting for Network Effects in Railway Asset Management. Journal of Transportation Engineering, 139(1), 92-100. doi:10.1061/(asce)te.1943-5436.0000477Gao, L., Guo, R., & Zhang, Z. (2013). An augmented Lagrangian decomposition approach for infrastructure maintenance and rehabilitation decisions under budget uncertainty. Structure and Infrastructure Engineering, 9(5), 448-457. doi:10.1080/15732479.2011.557388Gerçek, H., Karpak, B., & Kılınçaslan, T. (2004). A multiple criteria approach for the evaluation of the rail transit networks in Istanbul. Transportation, 31(2), 203-228. doi:10.1023/b:port.0000016572.41816.d2Goverde, R. M. P. (2010). A delay propagation algorithm for large-scale railway traffic networks. Transportation Research Part C: Emerging Technologies, 18(3), 269-287. doi:10.1016/j.trc.2010.01.002Grimes, G. A., & Barkan, C. P. L. (2006). Cost-Effectiveness of Railway Infrastructure Renewal Maintenance. Journal of Transportation Engineering, 132(8), 601-608. doi:10.1061/(asce)0733-947x(2006)132:8(601)Harker, P. T., & Vargas, L. G. (1990). Reply to «Remarks on the Analytic Hierarchy Process» by J. S. Dyer. Management Science, 36(3), 269-273. doi:10.1287/mnsc.36.3.269Huisman, T., & Boucherie, R. J. (2001). Running times on railway sections with heterogeneous train traffic. Transportation Research Part B: Methodological, 35(3), 271-292. doi:10.1016/s0191-2615(99)00051-xHwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems. doi:10.1007/978-3-642-48318-9Ieda, H., Kanayama, Y., Ota, M., Yamazaki, T., & Okamura, T. (2001). How can the quality of rail services in Tokyo be further improved? Transport Policy, 8(2), 97-106. doi:10.1016/s0967-070x(01)00002-6Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert Systems with Applications. doi:10.1016/j.eswa.2011.04.143Ishizaka, A., & Nemery, P. (2013). Multi-Criteria Decision Analysis. doi:10.1002/9781118644898Ivanović, I., Grujičić, D., Macura, D., Jović, J., & Bojović, N. (2013). One approach for road transport project selection. Transport Policy, 25, 22-29. doi:10.1016/j.tranpol.2012.10.001Johansson, P., & Nilsson, J.-E. (2004). An economic analysis of track maintenance costs. Transport Policy, 11(3), 277-286. doi:10.1016/j.tranpol.2003.12.002Kabir, G., Sadiq, R., & Tesfamariam, S. (2013). A review of multi-criteria decision-making methods for infrastructure management. Structure and Infrastructure Engineering, 10(9), 1176-1210. doi:10.1080/15732479.2013.795978Karanik, M., Wanderer, L., Gomez-Ruiz, J. A., & Pelaez, J. I. (2016). Reconstruction methods for AHP pairwise matrices: How reliable are they? Applied Mathematics and Computation, 279, 103-124. doi:10.1016/j.amc.2016.01.008Karydas, D. M., & Gifun, J. F. (2006). A method for the efficient prioritization of infrastructure renewal projects. Reliability Engineering & System Safety, 91(1), 84-99. doi:10.1016/j.ress.2004.11.016Kułakowski, K. (2015). Notes on order preservation and consistency in AHP. European Journal of Operational Research, 245(1), 333-337. doi:10.1016/j.ejor.2015.03.010Kumar, G., & Maiti, J. (2012). Modeling risk based maintenance using fuzzy analytic network process. Expert Systems with Applications, 39(11), 9946-9954. doi:10.1016/j.eswa.2012.01.004Lee, A. H. I., Chen, H. H., & Kang, H.-Y. (2009). Operations management of new project development: innovation, efficient, effective aspects. Journal of the Operational Research Society, 60(6), 797-809. doi:10.1057/palgrave.jors.2602605LEE, A. H. I., KANG, H.-Y., & CHANG, C.-C. (2011). AN INTEGRATED INTERPRETIVE STRUCTURAL MODELING–FUZZY ANALYTIC NETWORK PROCESS–BENEFITS, OPPORTUNITIES, COSTS AND RISKS MODEL FOR SELECTING TECHNOLOGIES. International Journal of Information Technology & Decision Making, 10(05), 843-871. doi:10.1142/s0219622011004592Liang, C., & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International Journal of Project Management, 26(8), 810-820. doi:10.1016/j.ijproman.2007.11.001Macharis, C., & Bernardini, A. (2015). Reviewing the use of Multi-Criteria Decision Analysis for the evaluation of transport projects: Time for a multi-actor approach. Transport Policy, 37, 177-186. doi:10.1016/j.tranpol.2014.11.002Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126-4148. doi:10.1016/j.eswa.2015.01.003Medury, A., & Madanat, S. (2013). Incorporating network considerations into pavement management systems: A case for approximate dynamic programming. Transportation Research Part C: Emerging Technologies, 33, 134-150. doi:10.1016/j.trc.2013.03.003Millet, I., & Saaty, T. L. (2000). On the relativity of relative measures – accommodating both rank preservation and rank reversals in the AHP. European Journal of Operational Research, 121(1), 205-212. doi:10.1016/s0377-2217(99)00040-5Nyström, B., & Söderholm, P. (2010). Selection of maintenance actions using the analytic hierarchy process (AHP): decision-making in railway infrastructure. Structure and Infrastructure Engineering, 6(4), 467-479. doi:10.1080/15732470801990209Olsson, N. O. E., Økland, A., & Halvorsen, S. B. (2012). Consequences of differences in cost-benefit methodology in railway infrastructure appraisal—A comparison between selected countries. Transport Policy, 22, 29-35. doi:10.1016/j.tranpol.2012.03.005Özgür, Ö. (2011). Performance analysis of rail transit investments in Turkey: İstanbul, Ankara, İzmir and Bursa. Transport Policy, 18(1), 147-155. doi:10.1016/j.tranpol.2010.07.004Özkır, V., & Demirel, T. (2012). A fuzzy assessment framework to select among transportation investment projects in Turkey. Expert Systems with Applications, 39(1), 74-80. doi:10.1016/j.eswa.2011.06.051Pardo-Bosch, F., & Aguado, A. (2014). Investment priorities for the management of hydraulic structures. Structure and Infrastructure Engineering, 11(10), 1338-1351. doi:10.1080/15732479.2014.964267Phillips, L. D., & Bana e Costa, C. A. (2007). Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing. Annals of Operations Research, 154(1), 51-68. doi:10.1007/s10479-007-0183-3Roy, B. (1991). The outranking approach and the foundations of electre methods. Theory and Decision, 31(1), 49-73. doi:10.1007/bf00134132Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. doi:10.1016/0377-2217(90)90057-iSaaty, T. L. (2006). Rank from comparisons and from ratings in the analytic hierarchy/network processes. European Journal of Operational Research, 168(2), 557-570. doi:10.1016/j.ejor.2004.04.032Saaty, T. L. (2008). Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas, 102(2), 251-318. doi:10.1007/bf03191825SAATY, T. L., & SAGIR, M. (2009). EXTENDING THE MEASUREMENT OF TANGIBLES TO INTANGIBLES. International Journal of Information Technology & Decision Making, 08(01), 7-27. doi:10.1142/s0219622009003247Saaty, T. L., & Shih, H.-S. (2009). Structures in decision making: On the subjective geometry of hierarchies and networks. European Journal of Operational Research, 199(3), 867-872. doi:10.1016/j.ejor.2009.01.064Saaty, T. L., & Tran, L. T. (2007). On the invalidity of fuzzifying numerical judgments in the Analytic Hierarchy Process. Mathematical and Computer Modelling, 46(7-8), 962-975. doi:10.1016/j.mcm.2007.03.022Saaty, T. L., & Vargas, L. G. (1993). Experiments on rank preservation and reversal in relative measurement. Mathematical and Computer Modelling, 17(4-5), 13-18. doi:10.1016/0895-7177(93)90171-tSalem, O. M., Miller, R. A., Deshpande, A. S., & Arurkar, T. P. (2013). Multi-criteria decision-making system for selecting an effective plan for bridge rehabilitation. 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An Agent-Based Intrusion Detection System for Local Area Networks

Since it is impossible to predict and identify all the vulnerabilities of a network beforehand, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs) are essential entities to ensure the security of a networked system. To be effective in carrying out their functions, the IDSs need to be accurate, adaptive, and extensible. Given these stringent requirements and the high level of vulnerabilities of the current days' networks, the design of an IDS has become a very challenging task. Although, an extensive research has been done on intrusion detection in a distributed environment, distributed IDSs suffer from a number of drawbacks e.g., high rates of false positives, low detection efficiency etc. In this paper, the design of a distributed IDS is proposed that consists of a group of autonomous and cooperating agents. In addition to its ability to detect attacks, the system is capable of identifying and isolating compromised nodes in the network thereby introducing fault-tolerance in its operations. The experiments conducted on the system have shown that it has a high detection efficiency and low false positives compared to some of the currently existing systems.Comment: 13 pages, 5 figures, 2 table

Mapping Fuzzy Petri Net to Fuzzy Extended Markup Language

Use of model gives the knowledge and information about the phenomenon also eradicates the cost, the effort and the hazard of using the real phenomenon. Characteristics and concepts of Petri nets are in a way that makes it simple and strong to describe and study the information processing system; especially it is shown in those which are dealing with discrete, concurrent, distributed, parallel and indecisive events. Yet, due to Petri nets inability to face with systems working on obscure data and continues events, the interest to develop fundamental concept of Petri nets has been raised which is led to new style of presented model named "fuzzy Petri nets". The difference in Petri nets is in the elements that have been fuzzed. Transitions, places, signs and arcs can be fuzzed. PMNL, on the other hand as a markup language has been engaged in uttering Petri nets in previous researches. Fuzzy markup nets can model the uncertainty of concurrent scenarios different from a dynamic system by a board of parameters and use of fuzzy membership dependencies. Therefore, in order to define these uncertain data, it is vital to use a formal language to describe fuzzy Petri nets. To support this version in this thesis, a markup language will be presented stating the structure and grammar of markup language and covering fuzzy concepts in Petri nets as well. Presenting the suggested grammar accommodates the support of fuzzy develope.DOI:http://dx.doi.org/10.11591/ijece.v3i5.403

A new paradigm for uncertain knowledge representation by Plausible Petri nets

This paper presents a new model for Petri nets (PNs) which combines PN principles with the foundations of information theory for uncertain knowledge representation. The resulting framework has been named Plausible Petri nets (PPNs). The main feature of PPNs resides in their efficiency to jointly consider the evolution of a discrete event system together with uncertain information about the system state using states of information. The paper overviews relevant concepts of information theory and uncertainty representation, and presents an algebraic method to formally consider the evolution of uncertain state variables within the PN dynamics. To illustrate some of the real-world challenges relating to uncertainty that can be handled using a PPN, an example of an expert system is provided, demonstrating how condition monitoring data and expert opinion can be modelled