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Добірка наукової літератури з теми "Soft Systems"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 9 червня 2025

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Статті в журналах з теми "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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2

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

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3

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

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4

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

Yu, GV, T. Chang, and JM White. "Soft tissue anchor systems." Journal of the American Podiatric Medical Association 84, no. 4 (April 1, 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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6

Brown, A. D. "Grounding soft systems research." European Journal of Information Systems 1, no. 6 (September 1992): 387–96. http://dx.doi.org/10.1057/ejis.1992.16.

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7

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

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8

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

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9

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

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10

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

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Дисертації з теми "Soft Systems"

1

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

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2

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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Анотація:

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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3

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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Анотація:

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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4

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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5

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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Анотація:

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.<br><p>Godkänd; 1998; 20060928 (evan)</p>

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6

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.<br>Doctor of Philosophy

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7

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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8

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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9

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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10

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. Gene expression (RT-PCR) measurements demonstrated that whilst zoledronic acid reduced cartilage degradation, S100A9 increased ECM breakdown. In a subsequent more substantive approach, a versatile polymer composite scaffold (variotis™) was designed and synthesised using a novel, high-throughput batch coagulation method. Methods were developed for formation of scaffolds with a range of shapes and properties. This novel scaffold could be readily post formed to impart graded interconnected porosity and mechanical response. Characterisation was undertaken for physical structure and mechanical behavior. The soft, elastic scaffolds were highly porous with excellent void interconnectivity and tensile properties within the range of skin. A range of novel bioactive glass compositions were developed for incorporation with the scaffolds. Glasses were analysed compositionally, mechanically, for bioactivity and radiopacity. During in vitro studies, composites with bioactive glass and bulk metallic glass constituents were shown to support fibroblast cell culture and exhibited less inflammation than stainless steel and cell controls, negligible inflammation. In vivo subcutaneous implantation of 124 polymer and polymer-composite variotis™ scaffolds into rats demonstrated complete tissue filling by 14 days. Histological staining confirmed high proportions of mature collagen content and vascularization within the polymer-Bioglass® composite scaffolds. Low inflammatory levels were confirmed by circulating and wound fluid cell counts.

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Книги з теми "Soft Systems"

1

Zelinka, Ivan, Roman Senkerik, Ganapati Panda, and 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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2

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

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3

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

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4

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

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5

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

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6

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

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7

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

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8

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

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9

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

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10

Rabin, Y., and 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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Частини книг з теми "Soft Systems"

1

Tettamanzi, Andrea, and Marco Tomassini. "Fuzzy Systems." In 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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2

Tettamanzi, Andrea, and Marco Tomassini. "Neuro-fuzzy Systems." In 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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3

Haynes, M. G. "Soft Systems Methodology." In Critical Issues in Systems Theory and Practice, 251–57. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-9883-8_35.

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4

Hicks, Michael J. "Soft Systems thinking." In 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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5

Checkland, Peter, and John Poulter. "Soft Systems Methodology." In 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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6

Daellenbach, Hans G., and Donald C. McNickle. "Soft Systems Thinking." In 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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7

Beynon-Davies, Paul. "Soft Systems Methodology." In Information Systems Development, 252–57. London: Macmillan Education UK, 1998. http://dx.doi.org/10.1007/978-1-349-14931-5_26.

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8

Checkland, Peter. "Soft systems methodology." In Encyclopedia of Operations Research and Management Science, 766–70. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_971.

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9

Jackson, Michael C. "Soft Systems Thinking." In 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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10

Checkland, Peter, and John Poulter. "Soft Systems Methodology." In 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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Тези доповідей конференцій з теми "Soft Systems"

1

Khoe, Y. S., and J. Stolk. "Generative Design of Soft-Armour." In Personal Armour Systems Symposium, 275–81. Brussels, Belgium: Royal Military Academy (Belgium), 2023. https://doi.org/10.52202/080042-0029.

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2

Morton, Chrys R., Sadan Wani, Ying Li, Jian Gao, Ruixin Qiu, Ryusuke Ishizaki, and John D. W. Madden. "Multi-layer soft capacitive sensors: soft vias save space and reduce exposed contacts." In Soft Mechatronics and Wearable Systems 2025, edited by Ilkwon Oh, 77. SPIE, 2025. https://doi.org/10.1117/12.3053230.

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3

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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4

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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7

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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Звіти організацій з теми "Soft Systems"

1

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

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2

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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Анотація:

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 systems methodologies by enhancing decision-making and facilitating effective communication among stakeholders.

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3

Hailperin, Max. Load Balancing for Massively-Parallel Soft-Real-Rime Systems. Fort Belvoir, VA: Defense Technical Information Center, September 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, December 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, April 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.), October 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 waterways, the Upper Mississippi River System, and Illinois River. Participants discussed their experience associated with designing and constructing islands with and on soft sediments prior to breakout sessions to discuss specific design and contracting elements. The groups were brought together to discuss design techniques that could be implemented in the Upper Mississippi River and Illinois River systems.

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Levy, Brian. How ‘Soft Governance’ Can Help Improve Learning Outcomes. Research on Improving Systems of Education (RISE), February 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 causes of learning shortfalls. Proximate causes include the skills and motivations of teachers, the quality of school management, the available of other inputs used in schools, and the extent to which learners come to school prepared to learn. Underlying these are the governance arrangements through which these inputs are deployed. Specialist knowledge on the proximate drivers of learning outcomes can straightforwardly be applied in countries where governance works well. However, in countries where the broader governance context is less supportive, specialist sector-specific interventions to support learning are less likely to add value. In these messy governance contexts, knowledge about the governance and political drivers of policymaking and implementation can be an important complement to sector-specific expertise. To help uncover new ways of improving learning outcomes (including in messy governance contexts), the Research on Improving Systems of Education (RISE) Programme has championed a broad-ranging, interdisciplinary agenda of research. RISE was organised around a variety of thematic and country-focused research teams that probed both proximate and underlying determinants of learning. As part of the RISE work programme, a political economy team commissioned studies on the politics of education policy adoption (the PET-A studies) for twelve countries (Chile, Egypt, Ethiopia, India, Indonesia, Kenya, Nigeria, Pakistan, Peru, South Africa, Tanzania and Vietnam). A December 2022 RISE synthesis of the individual country studies1 laid out and applied a framework for systematically assessing how political and institutional context influences learning outcomes—and used the results to suggest some ‘good fit’ soft governance entry points for improving learning outcomes across a variety of different contexts. This insight note elaborates on the synthesis paper’s argument and its practical implications.

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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), November 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), October 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), November 2012. http://dx.doi.org/10.2172/1059144.

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