Relevant bibliographies by topics / Rule based systems

Academic literature on the topic 'Rule based systems'

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Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Rule based systems"

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Hayes-Roth, Frederick. "Rule-based systems." Communications of the ACM 28, no. 9 (September 1985): 921–32. http://dx.doi.org/10.1145/4284.4286.

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G, Manju. "Rule-based Cognitive Modelling for Multimodal Intelligent Tutoring Systems." International Journal of Psychosocial Rehabilitation 24, no. 1 (January 20, 2020): 1754–60. http://dx.doi.org/10.37200/ijpr/v24i1/pr200275.

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Jokste, Lauma, and Janis Grabis. "RULE BASED ADAPTATION: LITERATURE REVIEW." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (June 15, 2017): 42. http://dx.doi.org/10.17770/etr2017vol2.2592.

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Rule based adaptive systems are growing in popularity and rules have been considered as an effective and elastic way to adapt systems. A rule based approach allows transparent monitoring of performed adaptation actions and gives an important advantage of easily modifiable adaptation process. The goal of this paper is to summarize literature review on rule based adaptation systems. The emphasis is put on rule types, semantics used for defining rules and measurement of effectiveness and correctness of rule based adaptation systems. The literature review has been done following a systematic approach consisting of three steps: planning, reviewing and analysis. Targeted research questions have been used to guide the review process. The review results are to be used for conducting further research in the area of rule based context-aware adaptive systems. This paper accents the potential of using rules as means to perform adaptive actions in enterprise applications taking into account contextual factors as well as points challenges, difficulties and open issues for planning, developing, implementing and running of such systems.
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HALAVATI, RAMIN, SAEED BAGHERI SHOURAKI, SIMA LOTFI, and POOYA ESFANDIAR. "SYMBIOTIC EVOLUTION OF RULE BASED CLASSIFIER SYSTEMS." International Journal on Artificial Intelligence Tools 18, no. 01 (February 2009): 1–16. http://dx.doi.org/10.1142/s0218213009000019.

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Evolutionary Algorithms are vastly used in development of rule based classifier systems in data mining where the rule base is usually a set of If-Then rules and an evolutionary trait develops and optimizes these rules. Genetic Algorithm is usually a favorite solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. Also, designing a good genetic algorithm for rule base evolution requires the design of a recombination operator that merges two rule bases without disrupting the functionalities of each of them. To overcome the speed problem and the need to design recombination operator, this paper presents a novel algorithm for rule base evolution based on natural process of symbiogenesis. The algorithm uses symbiotic combination operator instead of traditional sexual recombination operator of genetic algorithms. This operator takes two chromosomes with different number of genes (rules here) and merges them by combining all the information content of both chromosomes. Using this operator results in two major advantages: First, it totally removes the need to design the recombination operator and therefore is easier to use; second, it outperforms traditional genetic algorithm both in emergence speed and classification rate, this is tested and presented on some globally used benchmarks.
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Finlay, P. N., Malcolm King, and A. Burnett. "Administering Rule Development in Rule-Based Expert Systems." Journal of the Operational Research Society 40, no. 2 (February 1989): 193. http://dx.doi.org/10.2307/2583238.

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Finlay, P. N., Malcolm King, and A. Burnett. "Administering Rule Development in Rule-Based Expert Systems." Journal of the Operational Research Society 40, no. 2 (February 1989): 193–98. http://dx.doi.org/10.1057/jors.1989.24.

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Lotfi, A., and M. Howarth. "Noninteractive fuzzy rule-based systems." Information Sciences 99, no. 3-4 (July 1997): 219–34. http://dx.doi.org/10.1016/s0020-0255(96)00271-x.

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Kogge, Peter, John Oldfield, Mark Brule, and Charles Stormon. "VLSI and rule-based systems." ACM SIGARCH Computer Architecture News 16, no. 5 (December 1988): 52–65. http://dx.doi.org/10.1145/65755.65761.

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Lotfi, A., M. Howarth, and J. B. Hull. "Orthogonal Fuzzy Rule-Based Systems: Selection of Optimum Rules." Neural Computing & Applications 9, no. 1 (May 30, 2000): 4–11. http://dx.doi.org/10.1007/s005210070029.

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Aiello, Aldo, Ernesto Burattini, and Guglielmo Tamburrini. "Purely neural, rule-based diagnostic systems. I. Production rules." International Journal of Intelligent Systems 10, no. 8 (1995): 735–49. http://dx.doi.org/10.1002/int.4550100804.

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Dissertations / Theses on the topic "Rule based systems"

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Wang, Olivier. "Adaptive Rules Model : Statistical Learning for Rule-Based Systems." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX037/document.

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Les Règles Métiers (Business Rules en anglais, ou BRs) sont un outil communément utilisé dans l’industrie pour automatiser des prises de décisions répétitives. Le problème de l’adaptation de bases de règles existantes à un environnement en constante évolution est celui qui motive cette thèse. Des techniques existantes d’Apprentissage Automatique Supervisé peuvent être utilisées lorsque cette adaptation se fait en toute connaissance de la décision correcte à prendre en toute circonstance. En revanche, il n’existe actuellement aucun algorithme, qu’il soit théorique ou pratique, qui puisse résoudre ce problème lorsque l’information connue est de nature statistique, comme c’est le cas pour une banque qui souhaite contrôler la proportion de demandes de prêt que son service de décision automatique fait passer à des experts humains. Nous étudions spécifiquement le problème d’apprentissage qui a pour objectif d’ajuster les BRs de façon à ce que les décisions prises aient une valeur moyenne donnée.Pour ce faire, nous considérons les bases de Règles Métiers en tant que programmes. Après avoir formalisé quelques définitions et notations dans le Chapitre 2, le langage de programmation BR ainsi défini est étudié dans le Chapitre 4, qui prouve qu’il n’existe pas d’algorithme pour apprendre des Règles Métiers avec un objectif statistique dans le cas général. Nous limitons ensuite le champ d’étude à deux cas communs où les BRs sont limités d’une certaine façon : le cas Borné en Itérations dans lequel, quelles que soit les données d’entrée, le nombre de règles exécutées en prenant la décision est inférieur à une borne donnée ; et le cas Linéaire Borné en Itérations dans lequel les règles sont de plus écrite sous forme Linéaire. Dans ces deux cas, nous produisons par la suite un algorithme d’apprentissage basé sur la Programmation Mathématique qui peut résoudre ce problème. Nous étendons brièvement cette formalisation et cet algorithme à d’autres problèmes d’apprentissage à objectif statistique dans le Chapitre 5, avant de présenter les résultats expérimentaux de cette thèse dans le Chapitre 6
Business Rules (BRs) are a commonly used tool in industry for the automation of repetitive decisions. The emerging problem of adapting existing sets of BRs to an ever-changing environment is the motivation for this thesis. Existing Supervised Machine Learning techniques can be used when the adaptation is done knowing in detail which is the correct decision for each circumstance. However, there is currently no algorithm, theoretical or practical, which can solve this problem when the known information is statistical in nature, as is the case for a bank wishing to control the proportion of loan requests its automated decision service forwards to human experts. We study the specific learning problem where the aim is to adjust the BRs so that the decisions are close to a given average value.To do so, we consider sets of Business Rules as programs. After formalizing some definitions and notations in Chapter 2, the BR programming language defined this way is studied in Chapter 3, which proves that there exists no algorithm to learn Business Rules with a statistical goal in the general case. We then restrain the scope to two common cases where BRs are limited in some way: the Iteration Bounded case in which no matter the input, the number of rules executed when taking the decision is less than a given bound; and the Linear Iteration Bounded case in which rules are also all written in Linear form. In those two cases, we later produce a learning algorithm based on Mathematical Programming which can solve this problem. We briefly extend this theory and algorithm to other statistical goal learning problems in Chapter 5, before presenting the experimental results of this thesis in Chapter 6. The last includes a proof of concept to automate the main part of the learning algorithm which does not consist in solving a Mathematical Programming problem, as well as some experimental evidence of the computational complexity of the algorithm
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Stackhouse, Christian Paul 1960. "AN ADAPTIVE RULE-BASED SYSTEM." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276534.

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Adaptive systems are systems whose characteristics evolve over time to improve their performance at a task. A fairly new area of study is that of adaptive rule-based systems. The system studied for this thesis uses meta-knowledge about rules, rulesets, rule performance, and system performance in order to improve its overall performance in a problem domain. An interesting and potentially important phenomenon which emerged is that the performance the system learns while solving a problem appears to be limited by an inherent break-even level of complexity. That is, the cost to the system of acquiring complexity does not exceed its benefit for that problem. If the problem is made more difficult, however, more complexity is required, the benefit of complexity becomes greater than its cost, and the system complexity begins increasing, ultimately to the new break-even point. There is no apparent ultimate limit to the complexity attainable.
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Clark, Gary George. "Rule-based integrated building management systems." Thesis, Brunel University, 1993. http://bura.brunel.ac.uk/handle/2438/5150.

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The introduction of building management systems in large buildings have improved the control of building services and provided energy savings. However, current building management systems are limited by the physical level of integration of the building's services and the lack of intelligence provided in the control algorithms. This thesis proposes a new approach to the design and operation of building management systems using rule-based artificial intelligence techniques. The main aim of is to manage the services in the building in a more co-ordinated and intelligent manner than is possible by conventional techniques. This approach also aims to reduce the operational cost of the building by automatically tuning the energy consumption in accordance with occupancy profile of the building. A rule-based design methodology is proposed for building management systems. The design adopts the integrated structure made possible by the introduction of a common communications network for building services. The 'intelligence' is coded in the form of rules in such a way that it is both independent of any specific building description and easy to facilitate subsequent modification and addition. This is achieved using an object-oriented approach and classifying the range of data available into defined classes. The rules are divided into two knowledge-bases which are concerned with the building's control and its facilities management respectively. A wide range of rule-based features are proposed to operate on this data structure and are classified in terms of the data classes on which they operate. The concepts presented in this thesis were evaluated using software simulations, mathematical analysis and some hardware implementation. The conclusions of this work are that a rule-based building management system could provide significant enhancements over existing systems in terms of energy savings and improvements for both the building's management staff and its occupants.
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Carden, Kenneth John. "Explanation in rule-based expert systems." Thesis, Rhodes University, 1988. http://hdl.handle.net/10962/d1002034.

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The ability of an expert system to explain its reasoning is fundamental to the system's credibility. Explanations become even more vital in systems which use methods of uncertainty propagation. The research documented here describes the development of an explanation sub-system which interfaces with the P.R.O. Expert System Toolkit. This toolkit has been used in the development of three small ecological expert systems. This project has involved adapting the results of research in the field of explanation-generation, to the requirements of the ecologist users. The subsystem contains two major components. The first lists the rules that fired during a consultation. The second component comprises routines responsible for quantifying the effects on the system conclusions of the answers given to questions. These latter routines can be used to perform sensitivity analyses on the answers given. The incorporation of such routines in small expert systems is quite unique
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Moi, Havard. "Rule-based control of manufacturing systems." Thesis, Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22190168.

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Selva, Valero Daniel. "Rule-based system architecting of Earth observation satellite systems." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/76089.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 399-412).
System architecting is concerned with exploring the tradespace of early, high-level, system design decisions with a holistic, value-centric view. In the last few years, several tools and methods have been developed to support the system architecting process, focusing on the representation of an architecture as a set of interrelated decisions. These tools are best suited for applications that focus on breadth - i.e., enumerating a large and representative part of the architectural tradespace -as opposed to depth - modeling fidelity. However, some problems in system architecting require good modeling depth in order to provide useful results. In some cases, a very large body of expert knowledge is required. Current tools are not designed to handle such large bodies of knowledge because they lack scalability and traceability. As the size of the knowledge base increases, it becomes harder: a) to modify existing knowledge or add new knowledge; b) to trace the results of the tool to the model assumptions or knowledge base. This thesis proposes a holistic framework for architecture tradespace exploration of large complex systems that require a large body of expert knowledge. It physically separates the different bodies of knowledge required to solve a system architecting problem (i.e., knowledge about the domain, knowledge about the class of optimization or search problem, knowledge about the particular instance of problem) by using a rule-based expert system. It provides a generic population-based heuristic algorithm for search, which can be augmented with rules that encode knowledge about the domain, or about the optimization problem or class of problems. It identifies five major classes of system architecting problems from the perspective of optimization and search, and provides rules to enumerate architectures and search through the architectural tradespace of each class. A methodology is also defined to assess the value of an architecture using a rule-based approach. This methodology is based on a decomposition of stakeholder needs into requirements and a systematic comparison between system requirements and system capabilities using the rules engine. The framework is applied to the domain of Earth observing satellite systems (EOSS). Three EOSS are studied in depth: the NASA Earth Observing System, the NRC Earth Science Decadal Survey, and the Iridium GEOscan program. The ability of the framework to produce useful results is shown, and specific insights and recommendations are drawn.
by Daniel Selva Valero.
Ph.D.
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Deedman, Galvin Charles. "Building rule-based expert systems in case-based law." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26137.

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This thesis demonstrates that it is possible to build rule-based expert systems in case-based law using a deep-structure analysis of the law and commercially available artificial intelligence tools. Nervous shock, an area of the law of negligence, was the domain chosen. The expert whose knowledge was used to build the system was Professor J.C. Smith of the Faculty of Law at the University of British Columbia
Law, Peter A. Allard School of
Graduate
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Wang, Jinchang. "Rule-based expert systems and discrete optimization." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/29358.

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Bottaci, L. "The modifiability of rule-based expert systems." Thesis, Brunel University, 1985. http://bura.brunel.ac.uk/handle/2438/5789.

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This thesis examines the claim that rule representations of knowledge are conveniently modified. The thesis falls into two parts and in the first, a precise notion of a convenient modification, called an extension, is developed and it is shown that extensible knowledge-bases are very convenient to modify and develop. We show that- rule representations of knowledge are extensible only if they incorporate a suitable organisation of knowledge. Furthermore, we show that non-rule representations with a suitable organisation of knowledge are also extensible. We therefore conclude that rule representations of knowledge are no more or less extensible than non-rule representations. In the second part, we consider the more pragmatic aspects of knowledge-base modifiability. In each of two detailed case studies, we compare the modifiability of a rule-based expert system with its "second generation” counterpart which incorporates non-rule representations of knowledge. We conclude that in practice the modifiability of extensible knowledge-bases can be compromised if the organisation of knowledge is represented obscurely. Above all, the thesis emphasizes the importance of the organisation of knowledge in an expert system.
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Shin, Hyun-Myung. "Rule-based systems approach to fixture design /." The Ohio State University, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487597424137913.

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Books on the topic "Rule based systems"

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Mendel, Jerry M. Uncertain Rule-Based Fuzzy Systems. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51370-6.

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Fitzpatrick, T. Control using rule based systems. Manchester: UMIST, 1990.

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Clark, Gary George. Rule-based integrated building management systems. Uxbridge: Brunel University, 1993.

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Liu, Han, Alexander Gegov, and Mihaela Cocea. Rule Based Systems for Big Data. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23696-4.

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Ligêza, Antoni. Logical Foundations for Rule-Based Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-32446-1.

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Logical foundations for rule-based systems. Berlin: Springer, 2006.

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Fuzzy rule based computer design. Boca Raton: CRC Press, 1996.

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Expert systems programming: Practical techniques for rule-based systems. New York: Wiley, 1989.

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Bottaci, Leonardo. The modifiability of rule-based expert systems. Uxbridge: Brunel University, 1985.

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Brankin, Cecelia. A comparison of rule based systems and case based systems for flowering plant identification. [s.l: The Author], 1996.

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Book chapters on the topic "Rule based systems"

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Flasiński, Mariusz. "Rule-Based Systems." In Introduction to Artificial Intelligence, 125–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40022-8_9.

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Hopgood, Adrian A. "Rule-Based Systems." In Intelligent Systems for Engineers and Scientists, 21–49. 4th ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003226277-2.

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Bárdossy, András, and Lucien Duckstein. "Rule systems." In Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological and Engineering Systems, 81–102. London: CRC Press, 2022. http://dx.doi.org/10.1201/9780138755133-4.

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Mohan, Chilukuri Krishna. "Rule Based Programming." In Frontiers of Expert Systems, 99–131. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4509-5_4.

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Tung, Anthony K. H. "Rule-Based Classification." In Encyclopedia of Database Systems, 1–4. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_559-2.

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Lamperti, Gianfranco, and Marina Zanella. "Rule-Based Diagnosis." In Diagnosis of Active Systems, 193–233. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0257-7_7.

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Tung, Anthony K. H. "Rule-based Classification." In Encyclopedia of Database Systems, 2459–62. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_559.

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Fürnkranz, Johannes. "Rule-based Methods." In Encyclopedia of Systems Biology, 1883–88. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_610.

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Tung, Anthony K. H. "Rule-Based Classification." In Encyclopedia of Database Systems, 3265–68. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_559.

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Kohlas, Jürg, and Paul-André Monney. "Rule-Based Systems With Unreliable Rules." In Lecture Notes in Economics and Mathematical Systems, 136–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-01674-9_6.

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Conference papers on the topic "Rule based systems"

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Yongjie Zhang and Ansheng Deng. "Redundancy rules reduction in rule-based knowledge bases." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382017.

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Zhou, Mou, Changjing Shang, Pu Zhang, Guobin Li, Shangzhu Jin, Jun Peng, and Qiang Shen. "Towards Rule-ranking Based Fuzzy Rule Interpolation." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494436.

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Baaj, Ismail. "Learning Rule Parameters of Possibilistic Rule-Based System." In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2022. http://dx.doi.org/10.1109/fuzz-ieee55066.2022.9882626.

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Tan, J., and J. Srivastava. "Efficient rule matching in large scale rule based systems." In Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences. IEEE, 1992. http://dx.doi.org/10.1109/hicss.1992.183187.

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Zhang, Te, Christian Wagner, and Jonathan M. Garibaldi. "Counterfactual rule generation for fuzzy rule-based classification systems." In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2022. http://dx.doi.org/10.1109/fuzz-ieee55066.2022.9882705.

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Sabharwal, Arvind, S. Sitharama Iyengar, G. de Saussure, and C. R. Weisbin. "Parallelism In Rule-Based Systems." In 1988 Technical Symposium on Optics, Electro-Optics, and Sensors, edited by Mohan M. Trivedi. SPIE, 1988. http://dx.doi.org/10.1117/12.946995.

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Samad. "Towards connectionist rule-based systems." In Proceedings of 1993 IEEE International Conference on Neural Networks (ICNN '93). IEEE, 1988. http://dx.doi.org/10.1109/icnn.1988.23968.

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Rwo-Hsi Wang and Mok. "Response-time bounds of rule-based programs under rule priority structure." In Proceedings Real-Time Systems Symposium. IEEE Comput. Soc. Press, 1994. http://dx.doi.org/10.1109/real.1994.342722.

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Bonatti, P. A., and F. Mogavero. "Comparing Rule-Based Policies." In 2008 IEEE Workshop on Policies for Distributed Systems and Networks - POLICY. IEEE, 2008. http://dx.doi.org/10.1109/policy.2008.16.

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Jie Zheng, Gang Cheng, Shoushan Li, Fang Kong, Chu-Ren Huang, and Guodong Zhou. "Pattern-based rule disambiguation." In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2015. http://dx.doi.org/10.1109/fskd.2015.7382156.

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Reports on the topic "Rule based systems"

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Dyer, Rosemary M., and Gerald L. Freeman. Rule-Based Systems for Visibility Forecasts. Fort Belvoir, VA: Defense Technical Information Center, April 1989. http://dx.doi.org/10.21236/ada214622.

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Rigotti, Christophe, Patrick Marcel, and Mohand-Saïd Hacid. A Rule-Based Data Manipulation Language for OLAP Systems. Aachen University of Technology, 1997. http://dx.doi.org/10.25368/2022.76.

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Parikh, Jo A., and Anne Werkheiser. Incorporating Geometric Constraints into Rule-Based Systems Using Nonlinear Optimization. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada275093.

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Schein, Jeffery, and Steven Bushby. A simulation study of a hierarchical, rule-based method for system-level fault detection and diagnostics in HVAC systems. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7216.

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Clausen, Jay, D. Moore, L. Cain, and K. Malinowski. VI preferential pathways : rule or exception. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41305.

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Trichloroethylene (TCE) releases from leaks and spills next to a large government building occurred over several decades with the most recent event occurring 20 years ago. In response to a perceived conventional vapor intrusion (VI) issue a sub-slab depressurization system (SSDS) was installed 6 years ago. The SSDS is operating within design limits and has achieved building TCE vapor concentration reductions. However, subsequent periodic TCE vapor spikes based on daily HAPSITE™ measurements indicate additional source(s). Two rounds of smoke tests conducted in 2017 and 2018 involved introduction of smoke into a sanitary sewer and storm drain manholes located on effluent lines coming from the building until smoke was observed exiting system vents on the roof. Smoke testing revealed many leaks in both the storm sewer and sanitary sewer systems within the building. Sleuthing of the VI source term using a portable HAPSITE™ indicate elevated vapor TCE levels correspond with observed smoke emanation from utility lines. In some instances, smoke odors were perceived but no leak or suspect pipe was identified suggesting the odor originates from an unidentified pipe located behind or enclosed in a wall. Sleuthing activities also found building roof materials explain some of the elevated TCE levels on the 2nd floor. A relationship was found between TCE concentrations in the roof truss area, plenum space above 2nd floor offices, and breathing zone of 2nd floor offices. Installation of an external blower in the roof truss space has greatly reduced TCE levels in the plenum and office spaces. Preferential VI pathways and unexpected source terms may be overlooked mechanisms as compared to conventional VI.
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Mracek Dietrich, Anna, and Ravi Rajamani. Unsettled Issues Regarding the Certification of Electric Aircraft. SAE International, March 2021. http://dx.doi.org/10.4271/epr2021007.

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The aerospace industry is beginning to grapple with the reality of certifying electric aircraft (EA), signaling the maturing of the field. Many players are ramping up their activities to respond to imminent technical, safety, and regulatory requirements. While there are gaps in EA knowledge as well as the processes for certifying them, some leading standards development organizations (SDOs) such as SAE International, ASTM International, and RTCA—ably supported by representatives from regulatory agencies—are stepping in to address many of these issues. Of special importance are the new rule changes in the normal category (14 CFR Part 23, Amendment 64) that shift from a prescriptive philosophy to “performance-based rules.” Regarding system knowledge, there has been a trend in the use electrical energy to power systems that have long employed mechanical hydraulics. In the new EA paradigm, these components will be employed at criticality levels not previously witnessed in conventional aircraft, calling for a specific set of certification demands. Unsettled Issues Regarding the Certification of Electric Aircraft tackles the certification challenges faced by EA manufacturers in both the small (normal) and large (transport) categories, addressing technical, business, and process issues.
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De Michele, Roberto, and Juan Cruz Vieyra. From Fishing to Catching: Developing Actionable Red Flags in Public Procurement to Prevent and Control Corruption. Inter-American Development Bank, December 2022. http://dx.doi.org/10.18235/0004595.

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How can entities responsible for public procurement more reliably detect collusion and other irregular behavior? Most of the existing red flag tools are based on ex post analysis of public procurement data and are not integrated into national procurement systems. This does not allow them to identify irregularities in a timely manner, negatively affecting the efficiency and transparency of public spending. This document describes the red flags solution implemented in Paraguay, which contributes to solving these problems. It combines rule-based and machine learning algorithms to provide public officials with accurate, real-time information to reliably detect irregularities in the procurement process, without reducing efficiency.
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Decleir, Cyril, Mohand-Saïd Hacid, and Jacques Kouloumdjian. A Database Approach for Modeling and Querying Video Data. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.90.

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Indexing video data is essential for providing content based access. In this paper, we consider how database technology can offer an integrated framework for modeling and querying video data. As many concerns in video (e.g., modeling and querying) are also found in databases, databases provide an interesting angle to attack many of the problems. From a video applications perspective, database systems provide a nice basis for future video systems. More generally, database research will provide solutions to many video issues even if these are partial or fragmented. From a database perspective, video applications provide beautiful challenges. Next generation database systems will need to provide support for multimedia data (e.g., image, video, audio). These data types require new techniques for their management (i.e., storing, modeling, querying, etc.). Hence new solutions are significant. This paper develops a data model and a rule-based query language for video content based indexing and retrieval. The data model is designed around the object and constraint paradigms. A video sequence is split into a set of fragments. Each fragment can be analyzed to extract the information (symbolic descriptions) of interest that can be put into a database. This database can then be searched to find information of interest. Two types of information are considered: (1) the entities (objects) of interest in the domain of a video sequence, (2) video frames which contain these entities. To represent these information, our data model allows facts as well as objects and constraints. We present a declarative, rule-based, constraint query language that can be used to infer relationships about information represented in the model. The language has a clear declarative and operational semantics. This work is a major revision and a consolidation of [12, 13].
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Lindell, Suzanne. Keyword Cluster Algorithm for Expert System Rule Bases. Fort Belvoir, VA: Defense Technical Information Center, June 1987. http://dx.doi.org/10.21236/ada183064.

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Bryant, Kendall J. Power Plant Fuel Consumption: A Linear and Rule Based System. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada202367.

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