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Relevant bibliographies by topics / Soft Systems

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Academic literature on the topic 'Soft Systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Soft Systems"

1

Checkland, Peter B. "Soft Systems Methodology." Human Systems Management 8, no. 4 (1989): 273–89. http://dx.doi.org/10.3233/hsm-1989-8405.

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Jackson, Ivan F., and David Hosking. "Soft information systems." Journal of Information Technology 5, no. 3 (1990): 141–50. http://dx.doi.org/10.1057/jit.1990.32.

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Baldwin, P. R. "Soft billiard systems." Physica D: Nonlinear Phenomena 29, no. 3 (1988): 321–42. http://dx.doi.org/10.1016/0167-2789(88)90034-6.

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Jackson, Ivan F., and David Hosking. "Soft Information Systems." Journal of Information Technology 5, no. 3 (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

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Yu, GV, T. Chang, and JM White. "Soft tissue anchor systems." Journal of the American Podiatric Medical Association 84, no. 4 (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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Brown, A. D. "Grounding soft systems research." European Journal of Information Systems 1, no. 6 (1992): 387–96. http://dx.doi.org/10.1057/ejis.1992.16.

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Malmsten, Martin. "Soft drug delivery systems." Soft Matter 2, no. 9 (2006): 760. http://dx.doi.org/10.1039/b608348j.

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Kirwan, Barry. "Soft systems, hard lessons." Applied Ergonomics 31, no. 6 (2000): 663–78. http://dx.doi.org/10.1016/s0003-6870(00)00041-7.

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Song, Qiang, and Antony Satyadas. "Soft systems at Alabama." Fuzzy Sets and Systems 65, no. 2-3 (1994): 328. http://dx.doi.org/10.1016/0165-0114(94)90032-9.

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Knauf, A. "On soft billiard systems." Physica D: Nonlinear Phenomena 36, no. 3 (1989): 259–62. http://dx.doi.org/10.1016/0167-2789(89)90084-5.

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Dissertations / Theses on the topic "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

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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

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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

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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 structur

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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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Boughton, Elizabeth Anne. "Development of Bioactive Soft Tissue Scaffold Systems." Thesis, University of Sydney, 2011. https://hdl.handle.net/2123/23174.

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There is a need for development of versatile soft tissue scaffolds which can interface with tissue junctions and a range of tissue architectures. Two approaches were developed. A bone capable ceramic scaffold was infused with gel and polymer components to suit cartilage resurfacing. Several biphasic prototypes were successfully developed and evaluated mechanically and biologically. Whilst they supported chondrocyte culture within the infused gel layer they lacked sufficient mechanical stability. Two therapeutic agents were investigated for potential roles in modulating cartilage degradation. G

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Books on the topic "Soft Systems"

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

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

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

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Jim, Scholes, and Checkland Peter, eds. Soft systems methodology in action. Wiley, 1999.

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Checkland, Peter. Soft systems methodology in action. Wiley, 1990.

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Checkland, Peter. Soft systems methodology: A 30-year retrospective. John Wiley, 1999.

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1968-, Abraham Ajith, Köppen Mario 1964-, and HIS 2001 (2001 : Adelaide, S. Aust.), eds. Hybrid information systems. Physica-Verlag, 2002.

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Marriwala, Nikhil, C. C. Tripathi, Shruti Jain, and Shivakumar Mathapathi, eds. Soft Computing for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1048-6.

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Gilbert, Jenny, and Simon Pratt-Adams. Soft Systems Methodology in Education. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99225-5.

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

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Book chapters on the topic "Soft Systems"

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

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

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Haynes, M. G. "Soft Systems Methodology." In Critical Issues in Systems Theory and Practice. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-9883-8_35.

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

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

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

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Beynon-Davies, Paul. "Soft Systems Methodology." In Information Systems Development. Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14931-5_26.

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Checkland, Peter. "Soft systems methodology." In Encyclopedia of Operations Research and Management Science. Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_971.

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

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

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Conference papers on the topic "Soft Systems"

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Khoe, Y. S., and J. Stolk. "Generative Design of Soft-Armour." In Personal Armour Systems Symposium. Royal Military Academy (Belgium), 2023. https://doi.org/10.52202/080042-0029.

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Morton, Chrys R., Sadan Wani, Ying Li, et al. "Multi-layer soft capacitive sensors: soft vias save space and reduce exposed contacts." In Soft Mechatronics and Wearable Systems 2025, edited by Ilkwon Oh. SPIE, 2025. https://doi.org/10.1117/12.3053230.

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Lonea, Alina Madalina, and Daniela Elena Popescu. "Security issues for GRID systems." In 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." In 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, and L. Coroiu. "Assessment of PLC systems dependability by assuming coverage." In 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., and Valentina Emilia Balas. "Adaptive gain sliding mode control in uncertain MIMO systems." In 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, and Nicolae Crisan. "Towards Cognitive Antenna Systems based on antenna-channel co-evolution." In 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, and Nemanja Nedic. "Hierarchical neural model for workflow scheduling in Utility Management Systems." In 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?" In 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., and M. Norouzi. "Soft Vectors in Soft Hypervector Spaces." In 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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Reports on the topic "Soft Systems"

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

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JOSI, Editor. How GPT Enhances Soft Systems Methodologies in Industrial Engineering. Industrial Engineering Department, Faculty of Engineering, Universitas Andalas, 2024. https://doi.org/10.25077/11122024-2.

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Industrial systems are rarely straightforward. They often involve complex, ill-structured problems influenced by human factors, organizational culture, and decision-making dynamics. These types of challenges, often addressed through soft systems methodologies, require innovative approaches to bridge gaps between technology, people, and processes. Generative Pre-trained Transformers (GPT), with their advanced natural language understanding capabilities, have emerged as a promising tool for optimizing soft systems in industrial engineering. In this post, we explore how GPT can support soft syste

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

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Liu, Shiqiang. High-Performance, Soft Magnetic Laminates for Aerospace Power Systems. Defense Technical Information Center, 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. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada456402.

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Calomeni, Alyssa, and Charles Theiling. Proceedings from the Soft Substrate Island Design Workshop. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47721.

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This report summarizes the activities of the Soft Substrate Design Workshop held virtually on 08 September 2021. The 28 participants from federal, state, local, and academic organizations discussed designing and constructing islands with soft sediments in inland waterways. They were introduced to the US Army Corps of Engineers’ (USACE) Engineering With Nature® (EWN®) initiative and the vision for Tri-County Planning Commission (Peoria, Illinois). An overview of collaborative projects using landscape architecture and EWN principles was provided. The focus of discussion was on two primary waterw

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Levy, Brian. How ‘Soft Governance’ Can Help Improve Learning Outcomes. Research on Improving Systems of Education (RISE), 2023. http://dx.doi.org/10.35489/bsg-rise-ri_2023/053.

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On the surface, global gains in educating children have been remarkable. Access has expanded enormously. So, too, has knowledge about ‘best practices’—both education-sector-specific knowledge about how students learn and successful teachers teach, and knowledge about ‘best practice’ arrangements for governing education systems. Yet the combination of access and knowledge has not translated into broad-based gains in learning outcomes. Why? In seeking to address this question, a useful point of departure is the 2018 Learning World Development Report’s distinction between proximate and underlying

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Ardani, Kristen, Robert Margolis, David Feldman, Sean Ong, Galen Barbose, and 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), 2012. http://dx.doi.org/10.2172/1172717.

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Friedman, B., K. Ardani, D. Feldman, R. Citron, R. Margolis, and 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), 2013. http://dx.doi.org/10.2172/1107461.

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Ardani, K., G. Barbose, R. Margolis, R. Wiser, D. Feldman, and 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), 2012. http://dx.doi.org/10.2172/1059144.

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