Relevant bibliographies by topics / Association rule

Academic literature on the topic 'Association rule'

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Published: 4 June 2021
Last updated: 14 March 2023

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Journal articles on the topic "Association rule"

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Ali, Nzar Abdulqader. "Finding minimum confidence threshold to avoid derived rules in association rule minin." Journal of Zankoy Sulaimani - Part A 17, no. 4 (August 30, 2015): 271–78. http://dx.doi.org/10.17656/jzs.10443.

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Thomas, Binu, and G. Raju. "A Novel Web Classification Algorithm Using Fuzzy Weighted Association Rules." ISRN Artificial Intelligence 2013 (December 19, 2013): 1–10. http://dx.doi.org/10.1155/2013/316913.

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In associative classification method, the rules generated from association rule mining are converted into classification rules. The concept of association rule mining can be extended in web mining environment to find associations between web pages visited together by the internet users in their browsing sessions. The weighted fuzzy association rule mining techniques are capable of finding natural associations between items by considering the significance of their presence in a transaction. The significance of an item in a transaction is usually referred as the weight of an item in the transaction and finding associations between such weighted items is called fuzzy weighted association rule mining. In this paper, we are presenting a novel web classification algorithm using the principles of fuzzy association rule mining to classify the web pages into different web categories, depending on the manner in which they appear in user sessions. The results are finally represented in the form of classification rules and these rules are compared with the result generated using famous Boolean Apriori association rule mining algorithm.
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Khurana, Garvit. "Association Rule Hiding using Hash Tree." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 787–89. http://dx.doi.org/10.31142/ijtsrd23037.

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Taniar, David, Wenny Rahayu, Vincent Lee, and Olena Daly. "Exception rules in association rule mining." Applied Mathematics and Computation 205, no. 2 (November 2008): 735–50. http://dx.doi.org/10.1016/j.amc.2008.05.020.

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Sasikala, D., and K. Premalatha. "Application of Class Based Association Rule Pruning to Generate Optimal Association Rules in Healthcare." Journal of Medical Imaging and Health Informatics 11, no. 11 (November 1, 2021): 2859–61. http://dx.doi.org/10.1166/jmihi.2021.3876.

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The association rule mining approach produces uninteresting association rules. When the set of association rules become large, it becomes less interesting to the user. In order to pick interesting association rules among peak volumes of found association rules, it is critical to aid the decision-maker with an efficient post-processing phase. Theymotivate the need for association analysis performance. Practically it is an overhead to analyze the large set of association rules. In this work, association rule pruning technique called Class Based Association Rule Pruning (CBARP). This pruning techniques is proposed to prune the weak association rules of the healthcare system. The results are compared with Semantic Tree Based Association Rule Mining (STAR) technique and it demonstrate that the CBARP method outperforms other methods for the given support values.
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Verykios, V. S., A. K. Elmagarmid, E. Bertino, Y. Saygin, and E. Dasseni. "Association rule hiding." IEEE Transactions on Knowledge and Data Engineering 16, no. 4 (April 2004): 434–47. http://dx.doi.org/10.1109/tkde.2004.1269668.

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KORPIPÄÄ, PANU. "Visualizing constraint-based temporal association rules." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, no. 5 (November 2001): 401–10. http://dx.doi.org/10.1017/s0890060401155034.

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When dealing with time continuous processes, the discovered association rules may change significantly over time. This often reflects a change in the process as well. Therefore, two questions arise: What kind of deviation occurs in the association rules over time, and how could these temporal rules be presented efficiently? To address this problem of representation, we propose a method of visualizing temporal association rules in a virtual model with interactive exploration. The presentation form is a three-dimensional correlation matrix, and the visualization methods used are brushing and glyphs. Interactive functions used for displaying rule attributes and exploring temporal rules are implemented by utilizing Virtual Reality Modeling Language v2 mechanisms. Furthermore, to give a direction of rule potential for the user, the rule statistical interestingness is evaluated on the basis of combining weighted characteristics of rule and rule matrix. A constraint-based association rule mining tool which creates the virtual model as an output is presented, including the most relevant experiences from the development of the tool. The applicability of the overall approach has been verified by using the developed tool for data mining on a hot strip mill of a steel plant.
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Varma, Sandeep, and LijiP I. "Secure Outsourced Association Rule Mining using Homomorphic Encryption." International Journal of Engineering Research and Science 3, no. 9 (September 30, 2017): 70–76. http://dx.doi.org/10.25125/engineering-journal-ijoer-sep-2017-22.

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G.Usha Rani, G. Usha Rani, R. Vijaya Prakash, and Prof A. Govardhan Prof. A. Govardhan. "Mining Multilevel Association Rule Using Pincer Search Algorithm." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 54–57. http://dx.doi.org/10.15373/22778179/may2013/21.

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Gandhimathi, D., and N. Anbazhagan. "Extracting of Positive and Negative Association Rules." International Journal of Emerging Research in Management and Technology 6, no. 8 (June 25, 2018): 421. http://dx.doi.org/10.23956/ijermt.v6i8.175.

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Association rules analysis is a basic technique to expose how items/patterns are associated to each other. There are two common ways to measure association such as Support and Confidence. Several methods have been proposed in the literature to diminish the number of extracted association rules. Association Rule Mining is one of the greatest current data mining techniques designed to group objects together from huge databases aiming to take out the motivating correlation and relation with massive quantity of data. Association rule mining is used to discover the associated patterns from datasets. In this paper, we propose association rules from new methods on web usage mining. Generally, web usage log structure has several records so we have to overcome those unwanted records from large dataset. First of all the pre-processed data from the NASA dataset is clustered by the popular K-Means algorithm. Subsequently, the matrix calculation is progressed on that data. Further, the associations are performed on filtered data and get rid of the final associated page results. Positive and negative association rules are gathered by using new algorithm with Annul Object (𝒜𝒪). Wherever the object “𝒜𝒪” is presented those rules are known as negative association rule. Otherwise, the rules are positive association rules.
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Dissertations / Theses on the topic "Association rule"

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Palanisamy, Senthil Kumar. "Association rule based classification." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050306-131517/.

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Thesis (M.S.)--Worcester Polytechnic Institute.
Keywords: Itemset Pruning, Association Rules, Adaptive Minimal Support, Associative Classification, Classification. Includes bibliographical references (p.70-74).
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Wong, Wai-kit. "Security in association rule mining." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B39558903.

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Wong, Wai-kit, and 王偉傑. "Security in association rule mining." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39558903.

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REN, XIAOHUI. "COMPARING QUANTITATIVE ASSOCIATION RULE METHODS." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1089133333.

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Qing, Yang. "Pruning and summarizing discovered time series association rules." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-31828.

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Sensors are widely used in all aspects of our daily life including factories, hospitals and even our homes. Discovering time series association rules from sensor data can reveal the potential relationship between different sensors which can be used in many applications. However, the time series association rule mining algorithms usually produce rules much more than expected. It’s hardly to under-stand, present or make use of the rules. So we need to prune and summarize the huge amount of rules. In this paper, a two-step pruning method is proposed to reduce both the number and redundancy in the large set of time series rules. Be-sides, we put forward the BIGBAR summarizing method to summarize the rules and present the results intuitively.
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Rantzau, Ralf. "Extended concepts for association rule discovery." [S.l. : s.n.], 1997. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB8937694.

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Zhang, Ya Klein Cerry M. "Association rule mining in cooperative research." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6540.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed January 26, 2010). Thesis advisor: Dr. Cerry M. Klein. Includes bibliographical references.
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Icev, Aleksandar. "DARM distance-based association rule mining." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0506103-132405.

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HajYasien, Ahmed. "Preserving Privacy in Association Rule Mining." Thesis, Griffith University, 2007. http://hdl.handle.net/10072/365286.

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With the development and penetration of data mining within different fields and disciplines, security and privacy concerns have emerged. Data mining technology which reveals patterns in large databases could compromise the information that an individual or an organization regards as private. The aim of privacy-preserving data mining is to find the right balance between maximizing analysis results (that are useful for the common good) and keeping the inferences that disclose private information about organizations or individuals at a minimum. In this thesis we present a new classification for privacy preserving data mining problems, we propose a new heuristic algorithm called the QIBC algorithm that improves the privacy of sensitive knowledge (as itemsets) by blocking more inference channels. We demonstrate the efficiency of the algorithm, we propose two techniques (item count and increasing cardinality) based on item-restriction that hide sensitive itemsets (and we perform experiments to compare the two techniques), we propose an efficient protocol that allows parties to share data in a private way with no restrictions and without loss of accuracy (and we demonstrate the efficiency of the protocol), and we review the literature of software engineering related to the associationrule mining domain and we suggest a list of considerations to achieve better privacy on software.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information and Communication Technology
Faculty of Engineering and Information Technology
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Marinica, Claudia. "Association Rule Interactive Post-processing using Rule Schemas and Ontologies - ARIPSO." Phd thesis, Université de Nantes, 2010. http://tel.archives-ouvertes.fr/tel-00912580.

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This thesis is concerned with the merging of two active research domains: Knowledge Discovery in Databases (KDD), more precisely the Association Rule Mining technique, and Knowledge Engineering (KE) with a main interest in knowledge representation languages developed around the Semantic Web. In Data Mining, the usefulness of association rule technique is strongly limited by the huge amount and the low quality of delivered rules. Experiments show that rules become almost impossible to use when their number exceeds 100. At the same time, nuggets are often represented by those rare (low support) unexpected association rules which are surprising to the user. Unfortunately, the lower the support is, the larger the volume of rules becomes. Thus, it is crucial to help the decision maker with an efficient technique to reduce the number of rules. To overcome this drawback, several methods have been proposed in the literature such as itemset concise representations, redundancy reduction, filtering, ranking and post-processing. Even though rule interestingness strongly depends on user knowledge and goals, most of the existing methods are generally based on data structure. For instance, if the user looks for unexpected rules, all the already known rules should be pruned. Or, if the user wants to focus on specific family of rules, only this subset of rules should be selected. In this context, we address two main issues: the integration of user knowledge in the discovery process and the interactivity with the user. The first issue requires defining an adapted formalism to express user knowledge with accuracy and flexibility such as ontologies in the Semantic Web. Second, the interactivity with the user allows a more iterative mining process where the user can successively test different hypotheses or preferences and focus on interesting rules. The main contributions of this work can be summarized as follows: (i) A model to represent user knowledge. First, we propose a new rule-like formalism, called Rule Schema, which allows the user to define his/her expectations regarding the rules through ontology concepts. Second, ontologies allow the user to express his/her domain knowledge by means of a high semantic model. Last, the user can choose among a set of Operators for interactive processing the one to be applied over each Rule Schema (i.e. pruning, conforming, unexpectedness, . . . ). (ii) A new post-processing approach, called ARIPSO (Association Rule Interactive Post-processing using rule Schemas and Ontologies), which helps the user to reduce the volume of the discovered rules and to improve their quality. It consists in an interactive process integrating user knowledge and expectations by means of the proposed model. At each step of ARIPSO, the interactive loop allows the user to change the provided information and to reiterate the post-processing phase which produces new results. (iii) The implementation in post-processing of the proposed approach. The developed tool is complete and operational, and it implements all the functionalities described in the approach. Also, it makes the connection between different elements like the set of rules and rule schemas stored in PMML/XML files, and the ontologies stored in OWL files and inferred by the Pellet reasoner. (iv) An adapted implementation without post-processing, called ARLIUS (Association Rule Local mining Interactive Using rule Schemas), consisting in an interactive local mining process guided by the user. It allows the user to focus on interesting rules without the necessity to extract all of them, and without minimum support limit. In this way, the user may explore the rule space incrementally, a small amount at each step, starting from his/her own expectations and discovering their related rules. (v) The experimental study analyzing the approach efficiency and the discovered rule quality. For this purpose, we used a real-life and large questionnaire database concerning customer satisfaction. For ARIPSO, the experimentation was carried out in complete cooperation with the domain expert. For different scenarios, from an input set of nearly 400 thousand association rules, ARIPSO filtered between 3 and 200 rules validated by the expert. Clearly, ARIPSO allows the user to significantly and efficiently reduce the input rule set. For ARLIUS, we experimented different scenarios over the same questionnaire database and we obtained reduced sets of rules (less than 100) with very low support.
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Books on the topic "Association rule"

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Zhang, Chengqi, and Shichao Zhang, eds. Association Rule Mining. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46027-6.

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Dass, Rajanish. Classification using association rules. Ahmedabad: Indian Institute of Management, 2008.

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Gkoulalas-Divanis, Aris, and Vassilios S. Verykios. Association Rule Hiding for Data Mining. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6569-1.

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Gkoulalas-Divanis, Aris. Association rule hiding for data mining. New York: Springer, 2010.

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Harte, Michael. Sectarianism and the G.A.A. in the contect of Rule 21. [S.l: The Author], 1999.

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Rule 42 and all that. Dublin: Gill & Macmillan, 2007.

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1930-, Doyle R. F., and MinDak Tug of War Association., eds. Official MinDak Tug of War Association rule book/training guide. Forest Lake, Minn: The Association, 1989.

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Kazienko, Przemysław. Associations: Discovery, analysis and applications. Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej, 2008.

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Colorado. Office of State Auditor. Performance audit, Modified Rule of 75 Early Retirement Program. [Denver, Colo: State of Colorado, Office of the State Auditor, 1988.

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1978-, Koh Yun Sing, and Rountree Nathan 1974-, eds. Rare association rule mining and knowledge discovery: Technologies for infrequent and critical event detection. Hershey, PA: Information Science Reference, 2010.

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Book chapters on the topic "Association rule"

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Kakas, Antonis C., David Cohn, Sanjoy Dasgupta, Andrew G. Barto, Gail A. Carpenter, Stephen Grossberg, Geoffrey I. Webb, et al. "Association Rule." In Encyclopedia of Machine Learning, 48–49. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_38.

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Fürnkranz, Johannes. "Association Rule." In Encyclopedia of Systems Biology, 47. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_838.

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Toivonen, Hannu. "Association Rule." In Encyclopedia of Machine Learning and Data Mining, 70–71. Boston, MA: Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_38.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Association Rule Analysis." In Machine Learning in Medicine, 105–13. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6886-4_11.

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Sarjon, Defit, and Noor Md Sap Mohd. "Association Rules Using Rough Set and Association Rule Methods." In Lecture Notes in Computer Science, 238–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45683-x_27.

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Bramer, Max. "Association Rule Mining I." In Principles of Data Mining, 237–51. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7307-6_16.

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Bramer, Max. "Association Rule Mining II." In Principles of Data Mining, 253–69. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7307-6_17.

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Bramer, Max. "Association Rule Mining I." In Principles of Data Mining, 237–51. London: Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-7493-6_16.

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Bramer, Max. "Association Rule Mining II." In Principles of Data Mining, 253–69. London: Springer London, 2020. http://dx.doi.org/10.1007/978-1-4471-7493-6_17.

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Oliveira, Stanley R. M., Osmar R. Zaïane, and Yücel Saygin. "Secure Association Rule Sharing." In Advances in Knowledge Discovery and Data Mining, 74–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24775-3_10.

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Conference papers on the topic "Association rule"

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Soni, Sunita, Jyothi Pillai, and O. P. Vyas. "An associative classifier using weighted association rule." In 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC). IEEE, 2009. http://dx.doi.org/10.1109/nabic.2009.5393687.

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Baez-Monroy, Vicente O., and Simon O'Keefe. "An Associative Memory for Association Rule Mining." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371304.

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Zhou, Ling, and Stephen Yau. "Association rule and quantitative association rule mining among infrequent items." In the 8th international workshop. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1341920.1341929.

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Yang, Pu-Tai, Kai-Hao Yang, Ching-Chi Chen, and Shwu-Min Horng. "Subjective Association Rule Mining." In ICMLC 2018: 2018 10th International Conference on Machine Learning and Computing. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3195106.3195174.

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Morimoto, Yasuhiko. "Optimized transitive association rule." In the 2005 ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1066677.1066799.

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Das, Amitabha, Wee-Keong Ng, and Yew-Kwong Woon. "Rapid association rule mining." In the tenth international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/502585.502665.

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Hidber, Christian. "Online association rule mining." In the 1999 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/304182.304195.

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Olaru, Andrei, Claudia Marinica, and Fabrice Guillet. "Local mining of Association Rules with Rule Schemas." In 2009 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2009. http://dx.doi.org/10.1109/cidm.2009.4938638.

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Davis, Warren L., Peter Schwarz, and Evimaria Terzi. "Finding representative association rules from large rule collections." In Proceedings of the 2009 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2009. http://dx.doi.org/10.1137/1.9781611972795.45.

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Kumar, M. Naresh, and B. Eswara Reddy. "Improved classification association rule mining." In Multi-Agent Systems (IAMA 2009). IEEE, 2009. http://dx.doi.org/10.1109/iama.2009.5228045.

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Reports on the topic "Association rule"

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Rodríguez Burgos, Ojel L. Freedom and the Rule of Law. Puerto Rico Institute for Economic Liberty, September 2022. http://dx.doi.org/10.53095/13582005.

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The word freedom is used constantly, but little understood; to understand it, it is important to see the State as a civil association of individuals, where different ways of living and purposes coexist. This coexistence depends on a rule of law, which allows individuals to pursue their conception of the good life consistent with the rules of the association. The freedom requires a rule of law, which allows free action and cooperation of individuals in the market and thus benefits the economy.
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Megersa, Kelbesa. Tax Transparency for an Effective Tax System. Institute of Development Studies (IDS), January 2021. http://dx.doi.org/10.19088/k4d.2021.070.

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This rapid review examines evidence on the transparency in the tax system and its benefits; e.g. rising revenue, strengthen citizen/state relationship, and rule of law. Improvements in tax transparency can help in strengthening public finances in developing countries that are adversely affected by COVID-19. The current context (i.e. a global pandemic, widespread economic slowdown/recessions, and declining tax revenues) engenders the urgency of improving domestic resource mobilisation (DRM) and the fight against illicit financial flows (IFFs). Even before the advent of COVID-19, developing countries’ tax systems were facing several challenges, including weak tax administrations, low taxpayer morale and “hard-to-tax” sectors. The presence of informational asymmetry (i.e. low tax transparency) between taxpayers and tax authorities generates loopholes for abuse of the tax system. It allows the hiding of wealth abroad with a limited risk of being caught. Cases of such behaviour that are exposed without proper penalty may result in a decline in the morale of citizens and a lower level of voluntary compliance with tax legislation. A number of high-profile tax leaks and scandals have undermined public confidence in the fairness of tax systems and generated a strong demand for effective counteraction and tax transparency. One of the key contributing factors to lower tax revenues in developing countries (that is linked to low tax transparency) is a high level of IFFs. These flows, including international tax evasion and the laundering of corruption proceeds, build a major obstacle to successful DRM efforts. Research has also identified an association between organisational transparency (e.g. transparency by businesses and tax authorities) and stakeholder trust (e.g. between citizens and the state). However, the evidence is mixed as to how transparency in particular influences trust and perceptions of trustworthiness.
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Barrera-Osorio, Felipe, Paul Gertler, Nozomi Nakajima, and Harry A. Patrinos. Promoting Parental Involvement in Schools: Evidence from Two Randomized Experiments. Research on Improving Systems of Education (RISE), January 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/060.

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Parental involvement programs aim to strengthen school-home relations with the goal of improving children’s educational outcomes. We examine the effects of a parental involvement program in Mexico, which provides parent associations with grants and information. We separately estimate the effect of the grants from the effect of the information using data from two randomized controlled trials conducted by the government during the rollout of the program. Grants to parent associations did not improve educational outcomes. Information to parent associations reduced disciplinary actions in schools, mainly by increasing parental involvement in schools and changing parenting behavior at home. The divergent results from grants and information are partly explained by significant changes in perceptions of trust between parents and teachers. Our results suggest that parental involvement interventions may not achieve their intended goal if institutional rules are unclear about the expectations of parents and teachers as parents increase their involvement in schools.
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Lazonick, William, and Matt Hopkins. Why the CHIPS Are Down: Stock Buybacks and Subsidies in the U.S. Semiconductor Industry. Institute for New Economic Thinking Working Paper Series, September 2021. http://dx.doi.org/10.36687/inetwp165.

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The Semiconductor Industry Association (SIA) is promoting the Creating Helpful Incentives to Produce Semiconductors (CHIPS) for America Act, introduced in Congress in June 2020. An SIA press release describes the bill as “bipartisan legislation that would invest tens of billions of dollars in semiconductor manufacturing incentives and research initiatives over the next 5-10 years to strengthen and sustain American leadership in chip technology, which is essential to our country’s economy and national security.” On June 8, 2021, the Senate approved $52 billion for the CHIPS for America Act, dedicated to supporting the U.S. semiconductor industry over the next decade. As of this writing, the Act awaits approval in the House of Representatives. This paper highlights a curious paradox: Most of the SIA corporate members now lobbying for the CHIPS for America Act have squandered past support that the U.S. semiconductor industry has received from the U.S. government for decades by using their corporate cash to do buybacks to boost their own companies’ stock prices. Among the SIA corporate signatories of the letter to President Biden, the five largest stock repurchasers—Intel, IBM, Qualcomm, Texas Instruments, and Broadcom—did a combined $249 billion in buybacks over the decade 2011-2020, equal to 71 percent of their profits and almost five times the subsidies over the next decade for which the SIA is lobbying. In addition, among the members of the Semiconductors in America Coalition (SIAC), formed specifically in May 2021 to lobby Congress for the passage of the CHIPS for America Act, are Apple, Microsoft, Cisco, and Google. These firms spent a combined $633 billion on buybacks during 2011-2020. That is about 12 times the government subsidies provided under the CHIPS for America Act to support semiconductor fabrication in the United States in the upcoming decade. If the Congress wants to achieve the legislation’s stated purpose of promoting major new investments in semiconductors, it needs to deal with this paradox. It could, for example, require the SIA and SIAC to extract pledges from its member corporations that they will cease doing stock buybacks as open-market repurchases over the next ten years. Such regulation could be a first step in rescinding Securities and Exchange Commission Rule 10b-18, which has since 1982 been a major cause of extreme income inequality and loss of global industrial competitiveness in the United States.
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Viswanathan, Meera, Jennifer Cook Middleton, Alison Stuebe, Nancy Berkman, Alison N. Goulding, Skyler McLaurin-Jiang, Andrea B. Dotson, et al. Maternal, Fetal, and Child Outcomes of Mental Health Treatments in Women: A Systematic Review of Perinatal Pharmacologic Interventions. Agency for Healthcare Research and Quality (AHRQ), April 2021. http://dx.doi.org/10.23970/ahrqepccer236.

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Background. Untreated maternal mental health disorders can have devastating sequelae for the mother and child. For women who are currently or planning to become pregnant or are breastfeeding, a critical question is whether the benefits of treating psychiatric illness with pharmacologic interventions outweigh the harms for mother and child. Methods. We conducted a systematic review to assess the benefits and harms of pharmacologic interventions compared with placebo, no treatment, or other pharmacologic interventions for pregnant and postpartum women with mental health disorders. We searched four databases and other sources for evidence available from inception through June 5, 2020 and surveilled the literature through March 2, 2021; dually screened the results; and analyzed eligible studies. We included studies of pregnant, postpartum, or reproductive-age women with a new or preexisting diagnosis of a mental health disorder treated with pharmacotherapy; we excluded psychotherapy. Eligible comparators included women with the disorder but no pharmacotherapy or women who discontinued the pharmacotherapy before pregnancy. Results. A total of 164 studies (168 articles) met eligibility criteria. Brexanolone for depression onset in the third trimester or in the postpartum period probably improves depressive symptoms at 30 days (least square mean difference in the Hamilton Rating Scale for Depression, -2.6; p=0.02; N=209) when compared with placebo. Sertraline for postpartum depression may improve response (calculated relative risk [RR], 2.24; 95% confidence interval [CI], 0.95 to 5.24; N=36), remission (calculated RR, 2.51; 95% CI, 0.94 to 6.70; N=36), and depressive symptoms (p-values ranging from 0.01 to 0.05) when compared with placebo. Discontinuing use of mood stabilizers during pregnancy may increase recurrence (adjusted hazard ratio [AHR], 2.2; 95% CI, 1.2 to 4.2; N=89) and reduce time to recurrence of mood disorders (2 vs. 28 weeks, AHR, 12.1; 95% CI, 1.6 to 91; N=26) for bipolar disorder when compared with continued use. Brexanolone for depression onset in the third trimester or in the postpartum period may increase the risk of sedation or somnolence, leading to dose interruption or reduction when compared with placebo (5% vs. 0%). More than 95 percent of studies reporting on harms were observational in design and unable to fully account for confounding. These studies suggested some associations between benzodiazepine exposure before conception and ectopic pregnancy; between specific antidepressants during pregnancy and adverse maternal outcomes such as postpartum hemorrhage, preeclampsia, and spontaneous abortion, and child outcomes such as respiratory issues, low Apgar scores, persistent pulmonary hypertension of the newborn, depression in children, and autism spectrum disorder; between quetiapine or olanzapine and gestational diabetes; and between benzodiazepine and neonatal intensive care admissions. Causality cannot be inferred from these studies. We found insufficient evidence on benefits and harms from comparative effectiveness studies, with one exception: one study suggested a higher risk of overall congenital anomalies (adjusted RR [ARR], 1.85; 95% CI, 1.23 to 2.78; N=2,608) and cardiac anomalies (ARR, 2.25; 95% CI, 1.17 to 4.34; N=2,608) for lithium compared with lamotrigine during first- trimester exposure. Conclusions. Few studies have been conducted in pregnant and postpartum women on the benefits of pharmacotherapy; many studies report on harms but are of low quality. The limited evidence available is consistent with some benefit, and some studies suggested increased adverse events. However, because these studies could not rule out underlying disease severity as the cause of the association, the causal link between the exposure and adverse events is unclear. Patients and clinicians need to make an informed, collaborative decision on treatment choices.
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Bizer, Kilian, and Martin Führ. Compact Guidelines: Practical Procedure in Interdisciplinary Institutional Analysis. Sonderforschungsgruppe Institutionenanalyse, 2015. http://dx.doi.org/10.46850/sofia.9783941627451.

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These guidelines compactly describe how an interdisciplinary institutional analysis is to be implemented in practice: Which steps of analysis and control have to be taken? Which research questions are important and which role do empirical results play in the analysis?The description will be based on the requirements that the legislator has to fulfil with regard to the estimation of effects (as it is regulated in § 44 of the Joint Rules of Procedure of the Federal Ministries (Gemeinsame Ges-chäftsordnung der Bundesministerien, GGO) and in the guidelines of the Eu-ropean Commission). The steps of analysis and examination outlined in this paper can be equally used in relation to institutional design problems in companies (like the ad-justment of determining factors regarding ‘Governance, Risk Management, Compliance’ – GRC), associations or authorities. At the end of the compact guidelines, key terms of institutional analysis will be explained in a glossary. The glossary further contains recommendations on secondary literature.
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Colomb, Claire, and Tatiana Moreira de Souza. Regulating Short-Term Rentals: Platform-based property rentals in European cities: the policy debates. Property Research Trust, May 2021. http://dx.doi.org/10.52915/kkkd3578.

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Short-term rentals mediated by digital platforms have positive and negative impacts that are unevenly distributed among socio-economic groups and places. Detrimental impacts on the housing market and quality of life of long-term residents have been particular contentious in some cities. • In the 12 cities studied in the report (Amsterdam, Barcelona, Berlin, Brussels, Lisbon, London, Madrid, Milan, Paris, Prague, Rome and Vienna), city governments have responded differently to the growth of short-term rentals. • The emerging local regulations of short-term rentals take multiple forms and exhibit various degrees of stringency, ranging from rare cases of laissez-faire to a few cases of partial prohibition or strict quantitative control. Most city governments have sought to find a middle-ground approach that differentiates between the professional rental of whole units and the occasional rental of one’s home/ primary residence. • The regulation of short-term rentals is contentious and highly politicised. Six broad categories of interest groups and non-state actors actively participate in the debates with contrasting positions: advocates of the ‘sharing’ or ‘collaborative’ economy; corporate platforms; professional organisatons of short-term rental operators; new associations of hosts or ‘home-sharers’; the hotel and hospitality industry; and residents’ associations/citizens’ movements. • All city governments face difficulties in implementing and enforcing the regulations, due to a lack of sufficient resources and to the absence of accurate and comprehensive data on individual hosts. That data is held by corporate platforms, which have generally not accepted to release it (with a few exceptions) nor to monitor the content of their listings against local rules. • The relationships between platforms and city governments have oscillated between collaboration and conflict. Effective implementation is impossible without the cooperation of platforms. • In the context of the European Union, the debate has taken a supranational dimension, as two pieces of EU law frame the possibility — and acceptable forms — of regulation of online platforms and of short-term rentals in EU member states: the 2000 E-Commerce Directive and the 2006 Services Directive. • For regulation to be effective, the EU legal framework should be revised to ensure platform account- ability and data disclosure. This would allow city (and other ti ers of) governments to effectively enforce the regulations that they deem appropriate. • Besides, national and regional governments, who often control the legislative framework that defines particular types of short-term rentals, need to give local governments the necessary tools to be able to exercise their ‘right to regulate’ in the name of public interest objectives.
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Tadmor, Yaakov, Zachary Lippman, David Jackson, and Dani Zamir. three crops test for the ODO breeding method. United States Department of Agriculture, November 2013. http://dx.doi.org/10.32747/2013.7594397.bard.

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Hybrid vigor is the leading concept that rules crops breeding for almost a century. Yet, the exact mechanism that underlies heterosis is not clear. Over dominance interaction between alleles is one of the possible explanations. Our preliminary results indicated that severe developmental mutations at the heterozygous state have significant potential to improve plant performance. This led us to propose the ‘ODO breeding method’ that is based replacing a parental line of a successful hybrid with its mutated from to improve hybrid performance. Our BARD research challenged this method in three crop systems: maize, tomato and melon. In maize we could not detect any effect of mutant heterozigosity on yield or yield components when hybrids were tested however when we analyzed the effect of heterozigosity in mutant genes at B73 genetic background we could detect ODO in yield components using certain mutants. Our results indicate that the potential of utilizing the ODO Breeding Method for maize remains unclear. In tomato we overcame technical problems we faced in creating an EMS mutation library in indeterminate glasshouse tomatoes and now we have in our hands advanced material to study the putative ODO hybrids. We transferred some of the promising ODO mutations from M82 to indeterminate glasshouse tomatoes and putative ODO hybrids are ready to be evaluated this winter. In addition, we tested the effect of In melon we compared putative ‘ODO hybrids’ with their isogenic hybrids lacking the mutant allele and our results indicated a potential for the ODO breeding method to improve yield, fruit number per plant, and carotenoids content. Additional experiments are required to estimate better the expected success percentage of the ODO breeding method in melon so that it will become a recommended practice for improving hybrid performance. Based on our results we can't yet recommend the 'ODO breeding method' as a general tool to improve hybrid performance and more efforts are necessary to evaluate the percent of success of this method. The increased carotenoid content we found in association with CRTISO heterozygosity is promising and additional experiments are currently being performed to characterize this finding.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Relationship Between ‘Civil Society’ and ‘Democratic Freedoms’. Institute of Development Studies, June 2022. http://dx.doi.org/10.19088/k4d.2022.086.

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Notwithstanding the point that definitions of ‘civil society’ and ‘democracy’ are themselves actively debated, this rapid review defines democracy as ‘liberal democracy’, which goes beyond elections to include liberal components such as equality before the law, individual liberties, rule of law, and independent judiciary and legislature that constrains the executive (Grahn and Lührmann, 2020, p.8). Civil society is defined as “an organizational layer of the polity that lies between the state and private life composed of voluntary associations of people joined together in common purpose” (Coppedge et al. 2016, p.413). Thus, this rapid review seeks to find out what evidence is there on the relationship between civil society and democratic freedoms? The overall sense from the vast array of literature that looks at the relationship between civil society and democratic freedoms is that civil society is important for democracy, but there is no “automatic flow” from one to the other. Rather, the relationship is contingent on the nature of civil society, in addition to other dynamic, context-specific factors. Most of the evidence found during this rapid review was in studies that break down this broad topic into smaller sub-questions. They tended to be case studies that look at specific elements of ‘democratic freedoms’ (e.g., human rights, or anti-corruption), focus on specific countries, or were related to specific mechanisms (e.g., collective action) or processes (e.g., democratic regression). Each of these sub-topics is itself a large and contested area of research. According to some scholars, these case studies are overwhelmingly positive about civil society’s relationship to liberal democratic norms and practices. Some studies show that democratic regression occurs where the demands of a highly mobilised civil society cannot be effectively channelled by the party system or occur in contexts characterised by ethnic and regional differences or socio-economic inequalities.
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