Bibliografías temáticas / Soft Systems

Literatura académica sobre el tema "Soft Systems"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 9 de febrero de 2022

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Artículos de revistas sobre el tema "Soft Systems"

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Checkland, Peter B. "Soft Systems Methodology". Human Systems Management 8, n.º 4 (1989): 273–89. http://dx.doi.org/10.3233/hsm-1989-8405.

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Jackson, Ivan F. y David Hosking. "Soft information systems". Journal of Information Technology 5, n.º 3 (septiembre de 1990): 141–50. http://dx.doi.org/10.1057/jit.1990.32.

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Jackson, Ivan F. y David Hosking. "Soft Information Systems". Journal of Information Technology 5, n.º 3 (septiembre de 1990): 141–50. http://dx.doi.org/10.1177/026839629000500304.

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This paper describes a category of information systems called ‘Soft information systems’. Basically these lie between conventional information systems in which data are well defined, and management support, and decision support systems. A soft system is a system which operates on soft data. Such data cover categories of information such as conjectures, predictions, feelings and opinions and are typically found in systems where there is some element of anticipation of the future. Such systems include career counselling systems, where clients have rather ‘fuzzy’ views of what they might wish to do, through to economic based systems used to predict levels of employment, inflation levels and interest rates etc. In between are management-type systems in which it is normally assumed that hard (i.e. factual) data are used, for instance in budgeting systems. The paper describes some previous work and the experimental systems which tested and explored the ideas involved as well as attempting to refine some of the techniques that can be used to deal with soft data.
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Baldwin, P. R. "Soft billiard systems". Physica D: Nonlinear Phenomena 29, n.º 3 (enero de 1988): 321–42. http://dx.doi.org/10.1016/0167-2789(88)90034-6.

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Yu, GV, T. Chang y JM White. "Soft tissue anchor systems". Journal of the American Podiatric Medical Association 84, n.º 4 (1 de abril de 1994): 157–70. http://dx.doi.org/10.7547/87507315-84-4-157.

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The concept of soft tissue attachment and reattachment has been addressed over the years through a variety of surgical techniques. This includes tendons and ligaments that have been detached both surgically and traumatically from their osseous origins or insertions. This study is designed to provide the reader with a comprehensive overview of current commercially available devices. Detailed descriptions of the various devices are provided along with a discussion of the advantages and disadvantages of each. Their application and use in reconstructive foot and ankle surgery are also discussed.
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Malmsten, Martin. "Soft drug delivery systems". Soft Matter 2, n.º 9 (2006): 760. http://dx.doi.org/10.1039/b608348j.

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Kirwan, Barry. "Soft systems, hard lessons". Applied Ergonomics 31, n.º 6 (diciembre de 2000): 663–78. http://dx.doi.org/10.1016/s0003-6870(00)00041-7.

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Brown, A. D. "Grounding soft systems research". European Journal of Information Systems 1, n.º 6 (septiembre de 1992): 387–96. http://dx.doi.org/10.1057/ejis.1992.16.

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Georgiou, Ion. "Unravelling soft systems methodology". International Journal of Economics and Business Research 9, n.º 4 (2015): 415. http://dx.doi.org/10.1504/ijebr.2015.069680.

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Stowell, Frank. "Soft systems and research". Kybernetes 38, n.º 6 (12 de junio de 2009): 879–96. http://dx.doi.org/10.1108/03684920910973144.

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Tesis sobre el tema "Soft Systems"

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Wharton, Ryland N. "Soft Information Systems". The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1339116092.

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Zhang, Wei. "Soft-input soft-output multiuser detection for coded wireless multiuser systems". Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/29276.

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Multiuser detection permits the joint detection of signals from multiple sources. An optimal multiuser detector for coded multiuser systems is usually practically infeasible due to the associated complexity. An iterative receiver consisting of a soft-input soft-output (SISO) multiuser detector and a bank of SISO single user decoders can provide a system performance which approaches to that of the single user system after many iterations. On the other hand, it has a feasible computational complexity. We first propose and analyze three types of SISO multiuser detectors, which are mainly based on the underlying ideas of the traditional (non-SISO) multiuser detectors. These are: decorrelators, linear minimum mean square error (MMSE) detectors and parallel decision feedback detectors. In contrast to these traditional detectors, our SISO multiuser detectors make good use of soft inputs provided by SISO single user decoders and in turn, provide soft outputs to them. The resulting system performance converges quickly, while keeping the computational complexity of the SISO detectors proportional to the number of users cubed. This is a significant complexity reduction in comparison to the optimal detector which has a complexity exponentially proportional to the number of users. Secondly, we consider adaptive SISO multiuser detection. As it is well known, the optimum and many suboptimum SISO multiuser detectors require a lot of a priori information of the multiuser system, such as all users' transmitted waveforms, relative delays as well as the channel impulse response. In this thesis, we apply adaptive algorithms in the SISO multiuser detector in order to avoid the need for this a priori information. We propose two adaptive SISO parallel decision feedback detectors based on the normalized least mean square (NLMS) and recursive least squares (RLS) algorithms for both synchronous and asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems. Compared with traditional non-SISO adaptive detectors, our SISO adaptive detectors effectively exploit the a priori information of coded symbols to further improve their convergence performance. This a priori information is obtained from a bank of single user decoders. Monte-Carlo simulation results are presented and compared. Moreover, we extend adaptive SISO parallel decision feedback detection to asynchronous DS-CDMA systems over slow frequency non-selective Rayleigh fading channels.
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Kiddie, Paul David. "Decentralised soft-security in distributed systems". Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/1731/.

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Existing approaches to intrusion detection in imperfect wireless environments employ local monitoring, but are limited by their failure to reason about the imprecise monitoring within a radio environment that arises from unidirectional links and collisions. This compounds the challenge of detecting subtle behaviour or adds to uncertainty in the detection strategies employed. A simulation platform was developed, based on the Jist/SWANS environment, adopting a robust methodology that employed Monte-Carlo sampling in order to evaluate intrusion detection systems (IDS). A framework for simulating adversaries was developed, which enabled wormholes, black holes, selfishness, flooding and data modification to be simulated as well as a random distribution thereof. A game theoretic inspired IDS, sIDS, was developed, which applied reasoning between the detection and response components of a typical IDS, to apply more appropriate local responses. The implementation of sIDS is presented within the context of a generic IDS framework for MANET. Results showed a 5-15% reduction in false response rate compared to a baseline IDS over a number of attacking scenarios. sIDS was extended with immune system inspired features, namely a response over multiple timescales, as employed by the innate and adaptive components of the immune system, and the recruitment of neighbouring agents to participate in a co-ordinated response to an intrusion. Results showed a true response rate of 95-100% for all simulated attack scenarios. For random misbehaviour and assisted black hole scenarios, PDR gains of up to 30% and 15% were observed respectively compared to the pure game theoretic approach, tracking the omniscient network performance in these scenarios. In all, this study has shown that applying game theoretic reasoning to existing detection methods results in better discrimination of benign nodes from adversaries, which can be used to bias network operation towards the benign nodes. When fused with immune system inspired features, the resulting IDS maintained this discrimination whilst substantially reducing attack efficacy.
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Holwell, Susan. "Soft systems methodology and its role in information systems". Thesis, Lancaster University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364316.

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Mirijamdotter, Anita. "A multi-modal systems extension to soft systems methodology". Doctoral thesis, Luleå, 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18309.

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This thesis develops a design method for social systems that do not fit the conventional industrial pattern and that consequently are not apt for regulation through mechanical means. It builds upon Soft Systems Methodology (SSM), one of the most widely used and well regarded of design methodologies. Yet, the systems science literature has identified some weaknesses in this methodology, and these have been confirmed in the critical evaluation and the empirical study of this thesis. It was found that SSM tends to be relativistic in normative issues, that its modelling is at times reductionistic and that there are philosophical inconsistencies between its different phases of design. THe task in this thesis has been to preserve the methodological strengths of SSM while at the same time attempt to correct its weakness by combining it with another systems sience approach: Multi-modal Systems Thinking. This approach incorporates a multi-dimensional framework of life and a management model to attain viability in social systems. The combination of SSM with this new framework results in a Multi-modal Soft Systems Methodology (Arvidsjaur Method for short) that has been tested empirically in a project for unemployed youth in Arvidsjaur, a small municipality in the north of Sweden. The Arvidsjaur Method is an effective tool in four ways. Firstly, it incorporates normative standards that overcome the criticisms regarding SSM's relativistic stance. Secondly, it enhances philosophical consistency in the complete design process. Thirdly, it provides a managerial design structure and fourthly, it offers a potential for designing systems that support a holistic, complete and dignified human life. Such an approach is also likely to assist us in appreciating different perspectives of our post- modern society and in making appropriate choices.

Godkänd; 1998; 20060928 (evan)

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Yang, Hee Doo. "Design, Manufacturing, and Control of Soft and Soft/Rigid Hybrid Pneumatic Robotic Systems". Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/100635.

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Soft robotic systems have recently been considered as a new approach that is in principle better suited for tasks where safety and adaptability are important. That is because soft materials are inherently compliant and resilient in the event of collisions. They are also lightweight and can be low-cost; in general, soft robots have the potential to achieve many tasks that were not previously possible with traditional robotic systems. In this paper, we propose a new manufacturing process for creating multi-chambered pneumatic actuators and robots. We focus on using fabric as the primary structural material, but plastic films can be used instead of textiles as well. We introduce two different methods to create layered bellows actuators, which can be made with a heat press machine or in an oven. We also describe origami-like actuators with possible corner structures. Moreover, the fabrication process permits the creation of soft and soft/rigid hybrid robotic systems, and enables the easy integration of sensors into these robots. We analyze various textiles that are possibly used with this method, and model bellows actuators including operating force, restoring force, and estimated geometry with multiple bellows. We then demonstrate the process by showing a bellows actuator with an embedded sensor and other fabricated structures and robots. We next present a new design of a multi-DOF soft/rigid hybrid robotic manipulator. It contains a revolute actuator and several roll-pitch actuators which are arranged in series. To control the manipulator, we use a new variant of the piece-wise constant curvature (PCC) model. The robot can be controlled using forward and inverse kinematics with embedded inertial measurement units (IMUs). A bellows actuator, which is a subcomponent of the manipulator, is modeled with a variable-stiffness spring, and we use the model to predict the behavior of the actuator. With the model, the roll-pitch actuator stiffnesses are measured in all directions through applying forces and torques. The stiffness is used to predict the behavior of the end effector. The robotic system introduced achieved errors of less than 5% when compared to the models, and positioning accuracies of better than 1cm.
Doctor of Philosophy
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Tapp, Thomas L. "Soft decision decoders for mobile messaging systems". Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/13416.

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Scholes, James. "Extending the application of Soft Systems Methodology". Thesis, Lancaster University, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292912.

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Tapp, Keith A. "Mapping democratic practice using soft systems methodologies /". [St. Lucia, Qld.], 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16138.pdf.

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Aldarmi, Saud Ahmed. "Scheduling soft-deadline real-time transactions". Thesis, University of York, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310917.

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Libros sobre el tema "Soft Systems"

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Kowszun, J. Soft-systems methodology. Bristol: The Staff College, 1992.

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Zelinka, Ivan, Roman Senkerik, Ganapati Panda y Padma Suresh Lekshmi Kanthan, eds. Soft Computing Systems. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1936-5.

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Brown, Andrew D. Grounding soft systems research. Manchester: Manchester Business School, 1991.

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Jim, Scholes y Checkland Peter, eds. Soft systems methodology in action. Chichester: Wiley, 1999.

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Checkland, Peter. Soft systems methodology in action. Chichester, West Sussex, England: Wiley, 1990.

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Azvine, Benham, Detlef D. Nauck y Nader Azarmi, eds. Intelligent Systems and Soft Computing. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10720181.

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Thutupalli, Shashi. Towards Autonomous Soft Matter Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00735-9.

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Rabin, Y. y R. Bruinsma, eds. Soft Order in Physical Systems. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2458-8.

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Purohit, Hemant J., Vipin Chandra Kalia y Ravi Prabhakar More, eds. Soft Computing for Biological Systems. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7455-4.

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Rabin, Y. Soft Order in Physical Systems. Boston, MA: Springer US, 1994.

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Capítulos de libros sobre el tema "Soft Systems"

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Tettamanzi, Andrea y Marco Tomassini. "Fuzzy Systems". En Soft Computing, 83–122. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04335-6_3.

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Tettamanzi, Andrea y Marco Tomassini. "Neuro-fuzzy Systems". En Soft Computing, 201–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04335-6_6.

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Hicks, Michael J. "Soft Systems thinking". En Problem Solving in Business and Management, 226–55. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-7148-7_12.

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Checkland, Peter y John Poulter. "Soft Systems Methodology". En Systems Approaches to Making Change: A Practical Guide, 201–53. London: Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-7472-1_5.

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Checkland, Peter y John Poulter. "Soft Systems Methodology". En Systems Approaches to Managing Change: A Practical Guide, 191–242. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-809-4_5.

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Bennetts, Peter D. C. y A. Trevor Wood-Harper. "Soft Systems Methodology". En Systems for Sustainability, 543–47. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-0265-8_89.

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Checkland, Peter. "Soft Systems Methodology". En Encyclopedia of Operations Research and Management Science, 1430–36. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_971.

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Daellenbach, Hans G. y Donald C. McNickle. "Soft Systems Thinking". En Management Science, 171–204. London: Macmillan Education UK, 2005. http://dx.doi.org/10.1007/978-0-230-80203-2_7.

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Bausch, Kenneth C. "Soft Systems Theory". En The Emerging Consensus in Social Systems Theory, 103–22. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1263-9_8.

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Jackson, Michael C. "Soft Systems Thinking". En Systems Methodology for the Management Sciences, 133–81. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4899-2632-6_6.

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Actas de conferencias sobre el tema "Soft Systems"

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Lonea, Alina Madalina y Daniela Elena Popescu. "Security issues for GRID systems". En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565622.

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Varkonyi-Koczy, Annamaria R. "Using TS fuzzy models in anytime control systems". En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565596.

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Gergely, E. I., Fl Popentiu-Vladicescu, H. Madsen y L. Coroiu. "Assessment of PLC systems dependability by assuming coverage". En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565627.

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Roopaei, M. y Valentina Emilia Balas. "Adaptive gain sliding mode control in uncertain MIMO systems". En 2009 3rd International Workshop on Soft Computing Applications (SOFA). IEEE, 2009. http://dx.doi.org/10.1109/sofa.2009.5254875.

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Cremene, Ligia Chira y Nicolae Crisan. "Towards Cognitive Antenna Systems based on antenna-channel co-evolution". En 2009 3rd International Workshop on Soft Computing Applications (SOFA). IEEE, 2009. http://dx.doi.org/10.1109/sofa.2009.5254857.

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Vukmirovic, Srdan, Aleksandar Erdeljan, Lendak Imre y Nemanja Nedic. "Hierarchical neural model for workflow scheduling in Utility Management Systems". En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565626.

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Teodorescu, Horia-Nicolai. "Fuzzy logic systems as approximators - where do we stand today?" En 2010 4th International Workshop on Soft Computing Applications (SOFA). IEEE, 2010. http://dx.doi.org/10.1109/sofa.2010.5565629.

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Dehghan, O. R. y M. Norouzi. "Soft Vectors in Soft Hypervector Spaces". En 2020 8th Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS). IEEE, 2020. http://dx.doi.org/10.1109/cfis49607.2020.9238694.

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Labrecque, Martin, Peter Yiannacouras y J. Gregory Steffan. "Scaling Soft Processor Systems". En 2008 16th International Symposium on Field-Programmable Custom Computing Machines (FCCM). IEEE, 2008. http://dx.doi.org/10.1109/fccm.2008.8.

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Zhao, Jianguo y Ali Abbas. "A Low-Cost Soft Coiled Sensor for Soft Robots". En ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9916.

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Soft robots made from soft materials can closely emulate biological system using simple soft mechanical structures. Compared with traditional rigid-link robots, they are safe to work with humans and can adapt to confined environments. As a result, they are widely used for various robotic locomotions and manipulations. Nevertheless, for soft robots, being able to sense its state to enable closed-loop control using soft sensors remains a challenge. Existing sensors include external sensors such as camera systems, electromagnetic tracking systems, and internal sensors such as optical fibers, conductive liquid, and carbon black filled strips. In this paper, we investigate a new soft sensor made from low-cost conductive nylon sewing threads. By continuously inserting twists into a thread under some weight, coils can be formed to enable a coiled soft sensor. The resistance of the sensor varies with the change of length. The fabrication and experiments for this new coiled sensor is described in this paper. Embedding this sensor to a 3D printed soft manipulator demonstrates the sensing capability. Compared to existing soft sensors, the coiled sensor is low-cost, easy to fabricate, and can also be used as an actuator. It can be embedded to any soft robot to measure the deformation for closed-loop feedback control.
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Informes sobre el tema "Soft Systems"

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Sherfy, Robert y John D. Tanner. Total Environmental Control Systems, Soft-Start and Soft-Start Variable Capacity Air Conditioners. Fort Belvoir, VA: Defense Technical Information Center, noviembre de 1987. http://dx.doi.org/10.21236/ada210719.

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Hailperin, Max. Load Balancing for Massively-Parallel Soft-Real-Rime Systems. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 1988. http://dx.doi.org/10.21236/ada200912.

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Liu, Shiqiang. High-Performance, Soft Magnetic Laminates for Aerospace Power Systems. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 2004. http://dx.doi.org/10.21236/ada430916.

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Jensen, E. D. Time/Utility Function Decomposition in Soft Real-Time Distributed Systems. Fort Belvoir, VA: Defense Technical Information Center, abril de 2004. http://dx.doi.org/10.21236/ada456402.

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Ardani, Kristen, Robert Margolis, David Feldman, Sean Ong, Galen Barbose y Ryan Wiser. Benchmarking Non-Hardware Balance-of-System (Soft) Costs for U.S. Photovoltaic Systems Using a Bottom-Up Approach and Installer Survey. Office of Scientific and Technical Information (OSTI), noviembre de 2012. http://dx.doi.org/10.2172/1172717.

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Friedman, B., K. Ardani, D. Feldman, R. Citron, R. Margolis y J. Zuboy. Benchmarking Non-Hardware Balance-of-System (Soft) Costs for U.S. Photovoltaic Systems, Using a Bottom-Up Approach and Installer Survey - Second Edition. Office of Scientific and Technical Information (OSTI), octubre de 2013. http://dx.doi.org/10.2172/1107461.

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Ardani, K., G. Barbose, R. Margolis, R. Wiser, D. Feldman y S. Ong. Benchmarking Non-Hardware Balance of System (Soft) Costs for U.S. Photovoltaic Systems Using a Data-Driven Analysis from PV Installer Survey Results. Office of Scientific and Technical Information (OSTI), noviembre de 2012. http://dx.doi.org/10.2172/1059144.

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Ghezel-Ayagh, Hossein. Reliable SOFC Systems. Office of Scientific and Technical Information (OSTI), diciembre de 2017. http://dx.doi.org/10.2172/1429267.

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Thornell, Travis, Charles Weiss, Sarah Williams, Jennifer Jefcoat, Zackery McClelland, Todd Rushing y Robert Moser. Magnetorheological composite materials (MRCMs) for instant and adaptable structural control. Engineer Research and Development Center (U.S.), noviembre de 2020. http://dx.doi.org/10.21079/11681/38721.

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Magnetic responsive materials can be used in a variety of applications. For structural applications, the ability to create tunable moduli from relatively soft materials with applied electromagnetic stimuli can be advantageous for light-weight protection. This study investigated magnetorheological composite materials involving carbonyl iron particles (CIP) embedded into two different systems. The first material system was a model cementitious system of CIP and kaolinite clay dispersed in mineral oil. The magnetorheological behaviors were investigated by using parallel plates with an attached magnetic accessory to evaluate deformations up to 1 T. The yield stress of these slurries was measured by using rotational and oscillatory experiments and was found to be controllable based on CIP loading and magnetic field strength with yield stresses ranging from 10 to 104 Pa. The second material system utilized a polystyrene-butadiene rubber solvent-cast films with CIP embedded. The flexible matrix can stiffen and become rigid when an external field is applied. For CIP loadings of 8% and 17% vol %, the storage modulus response for each loading stiffened by 22% and 74%, respectively.
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Garner, James M., Bernard J. Guidos, Robert A. Phillabaum, Peter C. Muller y Eric Scheper. A Soft Recovery System Coupled With Advanced Diagnostics. Fort Belvoir, VA: Defense Technical Information Center, octubre de 2006. http://dx.doi.org/10.21236/ada456551.

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