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Journal articles on the topic 'Planning and problem solving'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Strohschneider, Stefan, and Dominik GÜss. "Planning and Problem Solving." Journal of Cross-Cultural Psychology 29, no. 6 (November 1998): 695–716. http://dx.doi.org/10.1177/0022022198296002.

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2

Anderson, Rita. "Planning and problem solving." Cancer Nursing 15, no. 1 (February 1992): 34???39. http://dx.doi.org/10.1097/00002820-199202000-00005.

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3

Hunt, Dennis, Philip R. de Lacey, and Bikkar S. Randhawa. "Problem Solving, Planning and Personality." International Journal of Psychology 22, no. 1 (January 1987): 97–110. http://dx.doi.org/10.1080/00207598708246770.

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4

Nemani, Ashish K., Suat Bog, and Ravindra K. Ahuja. "Solving the Curfew Planning Problem." Transportation Science 44, no. 4 (November 2010): 506–23. http://dx.doi.org/10.1287/trsc.1100.0323.

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5

Gunzelmann, Glenn, and John R. Anderson. "Problem solving: Increased planning with practice." Cognitive Systems Research 4, no. 1 (March 2003): 57–76. http://dx.doi.org/10.1016/s1389-0417(02)00073-6.

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6

Barton Cunningham, J. "Leadership in Planning and Problem Solving." Leadership & Organization Development Journal 12, no. 4 (April 1991): 22–27. http://dx.doi.org/10.1108/01437739110006936.

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7

hasoon, safwan. "Rule Based Planning for Solving Hanoi Problem." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 4 (December 1, 2013): 51–59. http://dx.doi.org/10.33899/csmj.2013.163546.

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8

Neely, Ann M. "Planning and Problem Solving in Teacher Education." Journal of Teacher Education 37, no. 3 (May 1986): 29–33. http://dx.doi.org/10.1177/002248718603700306.

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9

Davis, D. "Complete Dentures: From Planning to Problem Solving." British Dental Journal 196, no. 12 (June 2004): 786. http://dx.doi.org/10.1038/sj.bdj.4811392.

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10

Gauvain, Mary, and Barbara Rogoff. "Collaborative problem solving and children's planning skills." Developmental Psychology 25, no. 1 (1989): 139–51. http://dx.doi.org/10.1037/0012-1649.25.1.139.

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11

Aftriyati, Lusi Wira, Yenita Roza, and Maimunah Maimunah. "ANALISIS KEMAMPUAN PEMECAHAN MASALAH BERDASARKAN MINAT BELAJAR MATEMATIKA SISWA SMA PEKANBARU PADA MATERI SPLTV." Jurnal Matematika, Statistika dan Komputasi 16, no. 2 (December 19, 2019): 226. http://dx.doi.org/10.20956/jmsk.v16i2.8515.

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The problem solving abilities of students in learning mathematics are still not well trained, and there are varying degrees of difficulty experienced by students in learning mathematics. Factors that influence the ability to solve problems include interest in learning. This study aims to analyze the ability of problem solving based on students' interest in learning mathematics. This type of research is a descriptive qualitative study, which was conducted at Babussalam Pekanbaru High School with research subjects coming from Class X MIPA 1 selected based on the level of problem solving skills a

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12

Kasriana, Kasriana, and Rasid Ode. "DESCRPTION OF TRIGONOMETRY PROBLEM SOLVING ABILITIES BASEN ON PERSONALITY TYPE AND MATHEMATICS LEARNING ANXIETY LEVELS OF THE STUDENT AT SMAN 6 MAKASSAR." Jurnal Daya Matematis 7, no. 1 (April 1, 2019): 91. http://dx.doi.org/10.26858/jds.v7i1.8849.

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This study aimed to describe the high school students in solving problems based on personality types and levels of anxiety learn. The subjects were students of class X SMA 6 Makassar with stratified sampling.The results showed that: (1) in understanding the problem, studentstype of idealist high anxiety levels did not write sufficient conditions and a necessary condition; (2) in planning problem solving, students are able to determine the relevant information to solve problems; (3) in carrying out the plan of solving the problem, the students do the problems in accordance with the troubleshoot

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13

Sari, Christina Kartika, Sutopo Sutopo, and Dyah Ratri Aryuna. "The Profile of Students’ Thinking in Solving Mathematics Problems Based on Adversity Quotient." JRAMathEdu (Journal of Research and Advances in Mathematics Education) 1, no. 1 (January 30, 2016): 36–48. http://dx.doi.org/10.23917/jramathedu.v1i1.1784.

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The purpose of this research was to know the thinking processes of climber, camper, and quitter high school students in solving mathematical problems. This research used a qualitative descriptive method. Subjects were determined by purposive sampling. The technique of collecting data was done by task-based interviews. Based on the results of data analysis it can be concluded that: (1) the profiles of climber’s thinking processes are: (a) assimilation and abstraction in understanding problems, (b) assimilation, accommodation, and abstraction in planning problem solving (c) assimilation, accommo

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14

Rahmawati, Nurina Kurniasari, S. B. Waluya, Rochmad Rochmad, and Isti Hidayah. "METACOGNITIVE SKILLS ANALYSIS OF STUDENTS IN INTEGRAL CALCULUS PROBLEM SOLVING." Jurnal Pendidikan Matematika dan IPA 12, no. 2 (July 26, 2021): 170. http://dx.doi.org/10.26418/jpmipa.v12i2.45052.

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This study aims to describe the profile of students' metacognitive skills in solving integral calculus problems seen from the aspects of planning, monitoring and evaluation metacognitive skills. The research method used is descriptive qualitative research methods. The subjects in this study were 3rd semester students who had taken courses or were taking calculus II courses for the 2020/2021 academic year which were carried out using purposive sampling technique. In this study, the instrument used was a test to measure the ability in solving integral calculus problems in the form of essay quest

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15

ISAKSEN, SCOTT G., and SIDNEY J. PARNES. "Curriculum Planning for Creative Thinking and Problem Solving." Journal of Creative Behavior 19, no. 1 (March 1985): 1–29. http://dx.doi.org/10.1002/j.2162-6057.1985.tb00400.x.

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16

Eichmann, Beate, Frank Goldhammer, Samuel Greiff, Liene Pucite, and Johannes Naumann. "The role of planning in complex problem solving." Computers & Education 128 (January 2019): 1–12. http://dx.doi.org/10.1016/j.compedu.2018.08.004.

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17

Fitria, Zahroatul, Tri Novita Irawati, and Sholahudin Al Ayubi. "The Analysis of Students' Difficulties in Problem Solving at Number Material During Online Learning." Jurnal Axioma : Jurnal Matematika dan Pembelajaran 6, no. 1 (January 28, 2021): 54–61. http://dx.doi.org/10.36835/axi.v6i1.940.

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During the current pandemic, the development of information and communication technology is very much needed in online learning. The problem in this study is how to describe the level of problem-solving abilities carried out by students in solving math problems on number material during online learning. This study aims to identify the difficulties of seventh grade students of SMP Nurul Chotib Wringinagung in learning mathematics on numbers. The type and approach in this research is descriptive research with a qualitative approach. The data collection techniques in this study were tests, interv

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18

Bertsimas, Dimitris, Allison Chang, Velibor V. Mišić, and Nishanth Mundru. "The Airlift Planning Problem." Transportation Science 53, no. 3 (May 2019): 773–95. http://dx.doi.org/10.1287/trsc.2018.0847.

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The U.S. Transportation Command (USTRANSCOM) is responsible for planning and executing the transportation of U.S. military personnel and cargo by air, land, and sea. The airlift planning problem faced by the air component of USTRANSCOM is to decide how requirements (passengers and cargo) will be assigned to the available aircraft fleet and the sequence of pickups and drop-offs that each aircraft will perform to ensure that the requirements are delivered with minimal delay and with maximum utilization of the available aircraft. This problem is of significant interest to USTRANSCOM because of th

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19

Smith, Philip J., Elaine McCoy, and Chuck Layton. "Design-Induced Error in Flight Planning." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 16 (October 1993): 1091–95. http://dx.doi.org/10.1177/154193129303701611.

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There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. A major concern in the introduction of such tools to support problem-solving, though, is the potential to introduce new errors due to the interaction of the person with these computer support tools. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our

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20

Rindah, Maharani Aji Kharisma, Sri Dwiastuti, and Yudi Rinanto. "Excretory system learning in senior high school: comparative analysis of students’ problem solving skills." Biosfer 12, no. 2 (November 17, 2019): 249–57. http://dx.doi.org/10.21009/biosferjpb.v12n2.249-257.

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Problem-solving skills are the skills essential for students to have. This research aimed to analyze the problem-solving skills of senior high school students in biology learning of excretory system topics. The method used was descriptive-quantitative. The data were collected using a problem-solving essay test. The subjects were the eleventh-grade students of senior high schools in Surakarta, who were divided into A category (upper class) and B category (low level). Based on the analysis result, it can be seen that the problem-solving skill achievement of the eleventh grade of A group includes

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21

Sukoriyanto, Sukoriyanto, Toto Nusantara, Subanji Subanji, and Tjang Daniel Chandra. "Students’ Errors in Solving the Permutation and Combination Problems Based on Problem Solving Steps of Polya." International Education Studies 9, no. 2 (January 25, 2016): 11. http://dx.doi.org/10.5539/ies.v9n2p11.

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<p class="apa">This article was written based on the results of a study evaluating students’ errors in problem solving of permutation and combination in terms of problem solving steps according to Polya. Twenty-five students were asked to do four problems related to permutation and combination. The research results showed that the students still did a mistake in understanding the problems related to permutation and combination, the students still made a mistake in planning problem solving related to permutation and combination, and the students still had a mistake in rechecking the probl

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22

Mu, Wangshu, and Daoqin Tong. "On solving large p-median problems." Environment and Planning B: Urban Analytics and City Science 47, no. 6 (December 9, 2019): 981–96. http://dx.doi.org/10.1177/2399808319892598.

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Incorporating big data in urban planning has great potential for better modeling of urban dynamics and more efficiently allocating limited resources. However, big data may present new challenges for problem solutions. This research focuses on the p-median problem, one of the most widely used location models in urban and regional planning. Similar to many other location models, the p-median problem is non-deterministic polynomial-time hard (NP-hard), and solving large-sized p-median problems is difficult. This research proposes a high performance computing-based algorithm, random sampling and s

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23

MORTEZAEE, MARZIYEH, and ALIREZA NAZEMI. "A WAVELET COLLOCATION SCHEME FOR SOLVING SOME OPTIMAL PATH PLANNING PROBLEMS." ANZIAM Journal 57, no. 4 (April 2016): 461–81. http://dx.doi.org/10.1017/s1446181116000067.

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We consider an approximation scheme using Haar wavelets for solving optimal path planning problems. The problem is first expressed as an optimal control problem. A computational method based on Haar wavelets in the time domain is then proposed for solving the obtained optimal control problem. A Haar wavelets integral operational matrix and a direct collocation method are used to find an approximate optimal trajectory of the original problem. Numerical results are also presented for several examples to demonstrate the applicability and efficiency of the proposed method.

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24

Odior, Andrew Oyakhobo. "An Approach for Solving Linear Fractional Programming Problems." International Journal of Engineering & Technology 1, no. 4 (August 15, 2012): 298. http://dx.doi.org/10.14419/ijet.v1i4.270.

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Linear fractional programming problems are useful tools in production planning, financial and corporate planning, health care and hospital planning and as such have attracted considerable research interest. The paper presents a new approach for solving a fractional linear programming problem in which the objective function is a linear fractional function, while the constraint functions are in the form of linear inequalities. The approach adopted is based mainly upon solving the problem algebraically using the concept of duality and partial fractions and an example is given to clarify the devel

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25

Unterrainer, Josef M., and Adrian M. Owen. "Planning and problem solving: From neuropsychology to functional neuroimaging." Journal of Physiology-Paris 99, no. 4-6 (June 2006): 308–17. http://dx.doi.org/10.1016/j.jphysparis.2006.03.014.

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26

Chan, R. H. T., P. K. S. Tam, and D. N. K. Leung. "Solving the motion planning problem by using neural networks." Robotica 12, no. 4 (July 1994): 323–33. http://dx.doi.org/10.1017/s0263574700017343.

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SUMMARYThis paper presents a new neural networks-based method to solve the motion planning problem, i.e. to construct a collision-free path for a moving object among fixed obstacles. Our ‘navigator’ basically consists of two neural networks: The first one is a modified feed-forward neural network, which is used to determine the configuration space; the moving object is modelled as a configuration point in the configuration space. The second neural network is a modified bidirectional associative memory, which is used to find a path for the configuration point through the configuration space whi

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27

Mohd Tahar, Siti Hajar, Shamshul Bahar Yaakob, Ahmad Shukri Fazil Rahman, and Amran Ahmed. "Solving financial allocation problem in distribution system expansion planning." Bulletin of Electrical Engineering and Informatics 8, no. 1 (March 1, 2019): 320–27. http://dx.doi.org/10.11591/eei.v8i1.1445.

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This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to

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28

Warneken, Felix, Jasmin Steinwender, Katharina Hamann, and Michael Tomasello. "Young children's planning in a collaborative problem-solving task." Cognitive Development 31 (July 2014): 48–58. http://dx.doi.org/10.1016/j.cogdev.2014.02.003.

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29

Funke, Douglas J., and Robert F. Bachert. "IDEF-O, a Tool for Planning and Problem Solving." Proceedings of the Human Factors Society Annual Meeting 29, no. 6 (October 1985): 561–65. http://dx.doi.org/10.1177/154193128502900609.

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30

Kapa, E. "Problem solving, planning ability and sharing processes with LOGO." Journal of Computer Assisted Learning 15, no. 1 (March 1999): 73–84. http://dx.doi.org/10.1046/j.1365-2729.1999.151077.x.

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31

Morikawa, Katsumi, and Nobuto Nakamura. "Method for Solving Large-Scale Capacitated Production Planning Problem." Transactions of the Japan Society of Mechanical Engineers Series C 60, no. 575 (1994): 2484–90. http://dx.doi.org/10.1299/kikaic.60.2484.

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32

Junedi, Beni, and Juliana Juliana. "PENERAPAN STRATEGI PEMBELAJARAN INTERAKTIF DENGAN TEKNIK PEMBELAJARAN KOLABORATIF SEND-A-PROBLEM TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIS SISWA KELAS IX SMP." MES: Journal of Mathematics Education and Science 4, no. 2 (June 26, 2019): 139–44. http://dx.doi.org/10.30743/mes.v4i2.1289.

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Abstract. Mathematical problem solving is a process that includes understanding problems, planning problem solving, solving problems and checking again. Writing this article aims to determine the mathematical problem solving abilities of students by applying interactive learning strategies with collaborative learning techniques a-problem and conventional learning. This study was a quasi-experimental study with a randomized subject design posttest only control group design. Data collection techniques in the form of essay tests by testing hypotheses using the t-test. The results of the hypothesi

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33

Lestari, Wahyu, Loviga Deni Pratama, and Jailani Jailani. "METACOGNITIVE SKILLS IN MATHEMATICS PROBLEM SOLVING." Jurnal Daya Matematis 6, no. 3 (February 28, 2019): 286. http://dx.doi.org/10.26858/jds.v6i3.8537.

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This study is a descriptive qualitative approach. The purpose of this study was to describe level metacognitive skills of students in solving the problem solving test item based on indicators that had been compiled. Metacognitive skills in this study form planning, monitoring, reflection aspect. Data analysis aimed to describe the students’ metacognitive skills. Then, the researcher categorized the students’ metacognitive skills into reflective use, strategic use, aware use, and tacit use. The data collection methods in this study were documentation, test, and interview. From 40 student spread

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34

Geiger, Martin Josef, Lucas Kletzander, and Nysret Musliu. "Solving the Torpedo Scheduling Problem." Journal of Artificial Intelligence Research 66 (September 2, 2019): 1–32. http://dx.doi.org/10.1613/jair.1.11303.

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The article presents a solution approach for the Torpedo Scheduling Problem, an operational planning problem found in steel production. The problem consists of the integrated scheduling and routing of torpedo cars, i. e. steel transporting vehicles, from a blast furnace to steel converters. In the continuous metallurgic transformation of iron into steel, the discrete transportation step of molten iron must be planned with considerable care in order to ensure a continuous material flow. The problem is solved by a Simulated Annealing algorithm, coupled with an approach of reducing the set

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35

Furelos-Blanco, Daniel, and Anders Jonsson. "Solving Multiagent Planning Problems with Concurrent Conditional Effects." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7594–601. http://dx.doi.org/10.1609/aaai.v33i01.33017594.

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In this work we present a novel approach to solving concurrent multiagent planning problems in which several agents act in parallel. Our approach relies on a compilation from concurrent multiagent planning to classical planning, allowing us to use an off-the-shelf classical planner to solve the original multiagent problem. The solution can be directly interpreted as a concurrent plan that satisfies a given set of concurrency constraints, while avoiding the exponential blowup associated with concurrent actions. Our planner is the first to handle action effects that are conditional on what other

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Garrett, Caelan Reed, Tomás Lozano-Pérez, and Leslie Pack Kaelbling. "FFRob: Leveraging symbolic planning for efficient task and motion planning." International Journal of Robotics Research 37, no. 1 (November 12, 2017): 104–36. http://dx.doi.org/10.1177/0278364917739114.

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Mobile manipulation problems involving many objects are challenging to solve due to the high dimensionality and multi-modality of their hybrid configuration spaces. Planners that perform a purely geometric search are prohibitively slow for solving these problems because they are unable to factor the configuration space. Symbolic task planners can efficiently construct plans involving many variables but cannot represent the geometric and kinematic constraints required in manipulation. We present the FFRob algorithm for solving task and motion planning problems. First, we introduce extended acti

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37

Garrett, Caelan Reed, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, and Tomás Lozano-Pérez. "Integrated Task and Motion Planning." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 265–93. http://dx.doi.org/10.1146/annurev-control-091420-084139.

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The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP). TAMP problems contain elements of discrete task planning, discrete–continuous mathematical programming, and continuous motion planning and thus cannot be effectively addressed by any of these fields directly. In this article, we define a class of TAMP problems and survey algorithms for solving them, characterizing the solution methods in terms of their s

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38

Nursyifaa, Elza Efriyani, and Eka Senjayawati. "MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIK SISWA MTS DENGAN MENGGUNAKAN PROBLEM POSING." JPMI (Jurnal Pembelajaran Matematika Inovatif) 1, no. 6 (November 1, 2018): 1055. http://dx.doi.org/10.22460/jpmi.v1i6.p1055-1062.

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The purpose of this research is to assess whether the improvement of students' mathematical problem solving skills using Problem Posing approach is better than those using ordinary learning. The population in this research is MTs Nurul Falah Cimahi. This research instrument in the form of a test of mathematical problem solving skills of five items. This research data is processed using software SPSS Version 22. Data analysis used is test of normality and test of two difference of mean. The result of this research stated that the achievement and improvement of problem solving skills of MTs stud

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39

Hassani, Zineb Ibn Majdoub, Abdellah El Barkany, Abdelouahhab Jabri, and Ikram El Abbassi. "Models for Solving Integrated Planning and Scheduling Problem: Computational Comparison." International Journal of Engineering Research in Africa 34 (January 2018): 161–70. http://dx.doi.org/10.4028/www.scientific.net/jera.34.161.

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This article concerns the integration of planning and scheduling production system. Planning and scheduling are usually treated separately because of their complexity. Scheduling largely depends on the production quantities computed at the production planning level. However, ignoring scheduling constraints in the tactical level leads to inconsistent decisions. So, it is important to integrate planning and scheduling to efficiently manage operations and to determine a realistic production plan for a given sequence of jobs on each machine. In this paper, we present some approaches proposed to so

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40

Abu Bakar, Mohd Rizam, Abdul Jabbar Khudhur Bakheet, Farah Kamil, Bayda Atiya Kalaf, Iraq T. Abbas, and Lee Lai Soon. "Enhanced Simulated Annealing for Solving Aggregate Production Planning." Mathematical Problems in Engineering 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/1679315.

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Simulated annealing (SA) has been an effective means that can address difficulties related to optimisation problems.SAis now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multiobjective linear programming model for APP and optimised bySA. During the course of optimising for the APP problem, it uncovered that the capability ofSAwas inadequate and its performance was substandard, particularly for a

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41

Mansouri, Masoumeh, Henrik Andreasson, and Federico Pecora. "HYBRID REASONING FOR MULTI-ROBOT DRILL PLANNING IN OPEN-PIT MINES." Acta Polytechnica 56, no. 1 (February 29, 2016): 47. http://dx.doi.org/10.14311/app.2016.56.0047.

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Fleet automation often involves solving several strongly correlated sub-problems, including task allocation, motion planning, and coordination. Solutions need to account for very specific, domaindependent constraints. In addition, several aspects of the overall fleet management problem become known only online. We propose a method for solving the fleet-management problem grounded on a heuristically-guided search in the space of mutually feasible solutions to sub-problems. We focus on a mining application which requires online contingency handling and accommodating many domainspecific constrain

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42

Caughron, Jay J., and Michael D. Mumford. "Project Planning: The Effects of Using Formal Planning Techniques on Creative Problem-Solving." Creativity and Innovation Management 17, no. 3 (September 2008): 204–15. http://dx.doi.org/10.1111/j.1467-8691.2008.00484.x.

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43

Volkema, Roger J. "Problem statements in managerial problem solving." Socio-Economic Planning Sciences 22, no. 5 (January 1988): 213–20. http://dx.doi.org/10.1016/0038-0121(88)90038-9.

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44

Fattal, Laura. "Into the Woods - environmental problem solving through STEAM lesson planning." STEAM 3, no. 1 (December 2017): 1–13. http://dx.doi.org/10.5642/steam.20170301.08.

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45

Morris, R. "Problem solving in schizophrenia: a specific deficit in planning ability." Schizophrenia Research 14, no. 3 (February 1995): 235–46. http://dx.doi.org/10.1016/0920-9964(94)00044-9.

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46

Ziebuhr, Mario, and Herbert Kopfer. "Solving an integrated operational transportation planning problem with forwarding limitations." Transportation Research Part E: Logistics and Transportation Review 87 (March 2016): 149–66. http://dx.doi.org/10.1016/j.tre.2016.01.006.

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47

Wolosewicz, Cathy, Stéphane Dauzère-Pérès, and Riad Aggoune. "A NEW APPROACH FOR SOLVING INTEGRATED PLANNING AND SCHEDULING PROBLEM." IFAC Proceedings Volumes 39, no. 3 (2006): 191–96. http://dx.doi.org/10.3182/20060517-3-fr-2903.00112.

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48

Brilliant, Eleanor L. "Community Planning and Community Problem Solving: Past, Present, and Future." Social Service Review 60, no. 4 (June 1986): 568–89. http://dx.doi.org/10.1086/644400.

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49

VALENTE, ANDRÉ, V. RICHARD BENJAMINS, and LELIANE NUNES DE BARROS. "A library of system-derived problem-solving methods for planning." International Journal of Human-Computer Studies 48, no. 4 (April 1998): 417–47. http://dx.doi.org/10.1006/ijhc.1997.0192.

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Wei, Hu, Alan T. Murray, and Ningchuan Xiao. "Solving the continuous space p-centre problem: planning application issues." IMA Journal of Management Mathematics 17, no. 4 (October 1, 2006): 413–25. http://dx.doi.org/10.1093/imaman/dpl009.

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