Bibliographies thématiques / Procedure learning

Littérature scientifique sur le sujet « Procedure learning »

Auteur : Grafiati
Publié le 14 mars 2023

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Articles de revues sur le sujet "Procedure learning"

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Zentall, Thomas R. « Social learning mechanisms ». Interaction Studies 12, no 2 (21 juillet 2011) : 233–61. http://dx.doi.org/10.1075/is.12.2.03zen.

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Social influence and social learning are important to the survival of many organisms, and certain forms of social learning also may have important implications for their underlying cognitive processes. The various forms of social influence and learning are discussed with special emphasis on the mechanisms that may be responsible for opaque imitation (the copying of a response that the observer cannot easily see when it produces the response). Three procedures are examined, the results of which may qualify as opaque imitation: the bidirectional control procedure, the two- action procedure, and the do-as-I-do procedure. Variables that appear to affect the emergence of opaque imitation are identified and other complex forms of response copying are discussed. Keywords: bidirectional control procedure; contagion; emulation; imitation; local enhancement; object movement reenactment; observational conditioning; opaque imitation; social enhancement; social facilitation; social influence; social learning; stimulus enhancement; two action procedure
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Mendelson, Shahar. « An Unrestricted Learning Procedure ». Journal of the ACM 66, no 6 (6 décembre 2019) : 1–42. http://dx.doi.org/10.1145/3361699.

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Tsaih, R. R. « The softening learning procedure ». Mathematical and Computer Modelling 18, no 8 (octobre 1993) : 61–64. http://dx.doi.org/10.1016/0895-7177(93)90163-s.

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Wang, Zizhuang. « Temporal-Related Convolutional-Restricted-Boltzmann-Machine Capable of Learning Relational Order via Reinforcement Learning Procedure ». International Journal of Machine Learning and Computing 7, no 1 (février 2017) : 1–8. http://dx.doi.org/10.18178/ijmlc.2017.7.1.610.

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Hill, Christine, Mohamad El Zein, Abhishek Agnihotri, Margo Dunlap, Angela Chang, Alison Agrawal, Sindhu Barola et al. « Endoscopic sleeve gastroplasty : the learning curve ». Endoscopy International Open 05, no 09 (septembre 2017) : E900—E904. http://dx.doi.org/10.1055/s-0043-115387.

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Abstract Background and study aims Endoscopic sleeve gastroplasty (ESG) is gaining traction as a minimally invasive bariatric treatment. Concern that the learning curve may be slow, even among those proficient in endoscopic suturing, is a barrier to widespread implementation of the procedure. Therefore, we aimed to define the learning curve for ESG in a single endoscopist experienced in endoscopic suturing who participated in a 1-day ESG training program. Patients and methods Consecutive patients who underwent ESG between February 2016 and November 2016 were included. The performing endoscopist, who is proficient in endoscopic suturing for non-ESG procedures, participated in a 1-day ESG training session before offering ESG to patients. The outcome measurements were length of procedure (LOP) and number of plications per procedure. Nonlinear regression was used to determine the learning plateau and calculate the learning rate. Results Twenty-one consecutive patients (8 males), with mean age 47.7 ± 11.2 years and mean body mass index 41.8 ± 8.5 kg/m2 underwent ESG. LOP decreased significantly across consecutive procedures, with a learning plateau at 101.5 minutes and a learning rate of 7 cases (P = 0.04). The number of plications per procedure also decreased significantly across consecutive procedures, with a plateau at 8 sutures and a learning rate of 9 cases (P < 0.001). Further, the average time per plication decreased significantly with consecutive procedures, reaching a plateau at 9 procedures (P < 0.001). Conclusions Endoscopists experienced in endoscopic suturing are expected to achieve a reduction in LOP and number of plications per procedure in successive cases, with progress plateauing at 7 and 9 cases, respectively.
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Gülüstan, Filiz. « Learning curve of septoplasty procedure ». Turkish Journal of Ear Nose and Throat 29, no 4 (31 janvier 2020) : 166–71. http://dx.doi.org/10.5606/tr-ent.2019.65265.

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Ammon, Kurt. « A learning procedure for mathematics ». Annals of Mathematics and Artificial Intelligence 8, no 3-4 (septembre 1993) : 407–23. http://dx.doi.org/10.1007/bf01530800.

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Mlodinow, Leonard D., et Ion O. Stamatescu. « An evolutionary procedure for machine learning ». International Journal of Computer & ; Information Sciences 14, no 4 (août 1985) : 201–19. http://dx.doi.org/10.1007/bf00997019.

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Sahdan, Shafizza, Alias Masek, Noor Atikah Zainal Abidin et Juliati Jusoh. « Preliminary Study : Self-Regulated Learning Procedure ». MATEC Web of Conferences 150 (2018) : 05008. http://dx.doi.org/10.1051/matecconf/201815005008.

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Self-regulated learning (SRL) is widely adopted by various educational institutions all over the world. A simple guideline is important and essential for the successful implementation of SRL that yields good results. Hence, a procedure and lesson plan of SRL for the subject of Principles of Management are developed and tested in a preliminary study. The objective of the preliminary study is to determine the reliability of the instruments so that the implementation procedure and lesson plan for the real study can be executed smoothly. This study was conducted for a cycle of SRL designed procedure. ANCOVA was used to analyse the effects of the procedure and lesson plan in relation to students’ motivation, metacognitive awareness and academic achievement. Based on the results of the preliminary study, the items reliability index using alpha cronbach was 0.92, indicated that the questionnaire was good and effective. Each variable was significantly different, indicated that the procedure and lesson plan have positive effects on motivation, metacognition, and academic achievement. In conclusion, the procedure and lesson plan of Principles of Management developed are ready for an actual study.
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Meehan, Anita M. « A Procedure for Learning Students' Names ». Teaching of Psychology 17, no 2 (avril 1990) : 125–26. http://dx.doi.org/10.1207/s15328023top1702_16.

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Thèses sur le sujet "Procedure learning"

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Koelker, Rachel Lee Ellis Janet. « Comparing a discriminative stimulus procedure to a pairing procedure conditioning neutral social stimuli to function as conditioned reinforcers / ». [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12143.

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Jossen, Quentin. « Unsupervised learning procedure for nonintrusive appliance load monitoring ». Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209369.

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There is a continuously growing amount of appliances and energy dependent services in households. To date, efforts have mostly focused on energy efficiency, however behavior changes are required for a more sustainable energy consumption. People therefore need to understand their consumption habits to be able to adapt them. Appliance-specific feedback is probably the most efficient way to impact behaviors, since people need to ‘see’ where their electricity goes. Smart meters, currently being extensively rolled out in Europe and in the U.S. are good potential candidates to provide end-users with

energy advice. The required functionalities must however be rapidly defined if they are expected to be integrated in the future massive roll out.

Nonintrusive appliance load monitoring aims to derive appliance-specific information from the aggregate electricity consumption. While techniques have been developed since the 80’s, those mainly address the identification of previously learned appliances, from a database. Building such a database is an intrusive and tedious process which should be avoided. Whereas most recent efforts have focused on unsupervised techniques to disambiguate energy consumption into individual appliances, they usually rely on prior information about measured appliances such as the number of appliances, the number of states in each appliance as well as the power they consume in each state. This information should ideally be learned from the data. This topic will be addressed in the present research.

This work will present a framework for unsupervised learning for nonintrusive appliance

load monitoring. It aims to discover information about appliances of a household solely from its aggregate consumption data, with neither prior information nor user intervention. The learning process can be segmented into five tasks: the detection of on/off switching, the extraction of individual load signatures, the identification of

recurrent signatures, the discovery of two-state electrical devices and, finally, the elaboration

of appliance models. The first four steps will be addressed in this paper.

The suite of algorithms proposed in this work allows to discover the set of two-states electrical loads from their aggregated consumption. This, along with the evaluation

of their operating sequences, is a prerequisite to learn appliance models from the data. Results show that loads consuming power down to some dozens of watts can be learned from the data. This should encourage future researchers to consider such an unsupervised learning.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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Sjöblom, Niklas. « Evolutionary algorithms in statistical learning : Automating the optimization procedure ». Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160118.

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Scania has been working with statistics for a long time but has invested in becoming a data driven company more recently and uses data science in almost all business functions. The algorithms developed by the data scientists need to be optimized to be fully utilized and traditionally this is a manual and time consuming process. What this thesis investigates is if and how well evolutionary algorithms can be used to automate the optimization process. The evaluation was done by implementing and analyzing four variations of genetic algorithms with different levels of complexity and tuning parameters. The algorithm subject to optimization was XGBoost, a gradient boosted tree model, applied to data that had previously been modelled in a competition. The results show that evolutionary algorithms are applicable in finding good models but also emphasizes the importance of proper data preparation.
Scania har länge jobbat med statistik men har på senare år investerat i att bli ett mer datadrivet företag och använder nu data science i nästan alla avdelningar på företaget. De algoritmer som utvecklas av data scientists måste optimeras för att kunna utnyttjas till fullo och detta är traditionellt sett en manuell och tidskrävade process. Detta examensarbete utreder om och hur väl evolutionära algoritmer kan användas för att automatisera optimeringsprocessen. Utvärderingen gjordes genom att implementera och analysera fyra varianter avgenetiska algoritmer med olika grader av komplexitet och trimningsparameterar. Algoritmen som var målet för optimering var XGBoost, som är en gradient boosted trädbaserad modell. Denna applicerades på data som tidigare hade modellerats i entävling. Resultatet visar att evolutionära algoritmer är applicerbara i att hitta bra modellermen påvisar även hur fundamentalt det är att arbeta med databearbetning innan modellering.
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Koelker, Rachel Lee. « Comparing a discriminative stimulus procedure to a pairing procedure : Conditioning neutral social stimuli to function as conditioned reinforcers ». Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12143/.

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Social stimuli that function as reinforcers for most children generally do not function as reinforcers for children diagnosed with autism. These important social stimuli include smiles, head nods, thumb-ups, and okay signs. It should be an important goal of therapy for children with autism to condition these neutral social stimuli to function as reinforcers for children diagnosed with autism. There is empirical evidence to support both a pairing procedure (classical conditioning) and a discriminative stimulus procedure to condition neutral stimuli to function as reinforcers. However, there is no clear evidence as to the superiority of effectiveness for either procedure. Despite this most textbooks and curriculum guides for children with autism state only the pairing procedure to condition neutral stimuli to function as reinforcers. Recent studies suggest that the discriminative stimulus procedure may in fact be more effective in conditioning neutral stimuli to function as reinforcers for children diagnosed with autism. The present research is a further comparison of these two procedures. Results from one participant support recent findings that suggest the discriminative stimulus procedure is more effective in conditioning neutral stimuli to function as reinforcers. But the results from the other participant show no effects from either procedure, suggesting future research into conditions necessary to condition neutral social stimuli to function as reinforcers for children with autism.
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Yetter, Georgette. « Acceptability of a student assistance team procedure to school staff ». Diss., [Lincoln, Neb. : University of Nebraska-Lincoln], 2003. http://www.unl.edu/libr/Dissertations/2003/YetterDis.pdf.

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Campbell, Fiona. « Imitative and nonimitative social learning using a two object/two action procedure ». Thesis, University College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327045.

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McManus, Jacqueline Law Faculty of Law UNSW. « Capacity-development at work : the contribution of workplace-based learning to tax administration ». Awarded by:University of New South Wales. School of Law, 2007. http://handle.unsw.edu.au/1959.4/29565.

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This study is concerned with workers, workplace learning and organisations. In the current climate of techno-logisation and globalisation, change is constant. Consequently, development of workers??? capacity to grow and adapt is essential for both the employability of the individual, and the economic survival of organisations. Capacity is considered essential because it encompasses more than current ability, it enables the growth of innovative approaches to work, which are required to adapt to change. Learning is central to capacity-development and so learning skills and related ???general skills??? are vital, but these skills must be developed in a specific context to be useful tools. Learning involves balancing the chaos of uncertainty and the old grooves of experience. Learning also involves personal growth. This study explores ways of helping workers develop capacity and especially learning skills, in a context of complexity, to meet the demands of their changing environment. The methodological approach taken is two fold, including both a conceptual and an empirical component. Firstly, a framework, based on conceptual innovation, is constructed to direct the design of workplace-based programs aimed at developing workers??? capacity. This is done as guidance in tailoring a program that promotes the development of an understanding of the necessary skills and knowledge in the context of the work undertaken, how to use them effectively, and the impact they have on the worker and their environment. It is contended that this framework promotes continued and sustained growth in workers??? skills and adaptability, that is, it develops capacity. Secondly, fieldwork based on a program developed for a group of tax administrators to instantiate this framework is reported. The findings show that this workplace-based program designed for the Australian Taxation Office has precipitated the development of the participant workers??? capacity, and in so doing, has shown the empirical significance of the conceptual innovation. Finally, the broader implications of developing workers??? capacity are explored. These include the need for organisational support for workers??? capacity-development, the possibility of the development of a learning culture in organisations, and the general applicability of the framework to other organisations, professions, and industries.
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Matoug, Mohamed Ibrahim. « Procedure-knowledge expectation (PKE) model : as an assessment tool for measuring bricklayer trainees' planning skill ». Thesis, University of Salford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335464.

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Ward, Lindsey L. « Exploring facets of classroom management to promote student learning routine, procedure, and teachers' belief systems / ». Theological Research Exchange Network (TREN), 2007. http://www.tren.com/search.cfm?p088-0193.

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Staff, Donald Michael Hyten Cloyd. « Utilizing staff training methods for developing a mathetics error correction procedure in a university classroom ». [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9735.

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Livres sur le sujet "Procedure learning"

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Stempel, Jeffrey W. Learning civil procedure. St. Paul, MN : West, 2013.

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Don, Stuart, dir. Learning Canadian criminal procedure. Toronto : Carswell, 1986.

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1943-, Stuart Don, dir. Learning Canadian criminal procedure. 5e éd. Scarborough, Ont : Carswell, 1998.

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1943-, Stuart Don, dir. Learning Canadian criminal procedure. 6e éd. Scarborough, Ont : Carswell, 2000.

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Delisle, R. J. Learning Canadian criminal procedure. 4e éd. Scarborough, Ont : Carswell, 1996.

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author, Quigley Tim, et Delisle R. J. author, dir. Learning Canadian criminal procedure. Toronto, Ontario : Carswell, a Division of Thomson Reuiters Canada Limited, 2013.

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1943-, Stuart Don, dir. Learning Canadian criminal procedure. 2e éd. Scarborough, Ont., Canada : Thomson Professional Pub. Canada, 1991.

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Delisle, R. J. Learning Canadian criminal procedure. Toronto : Carswell, 1986.

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author, Quigley Tim, dir. Learning Canadian criminal procedure. Toronto, Ontario : Thomson Reuters, 2016.

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Delisle, R. J. Learning Canadian criminal procedure. 3e éd. Scarborough, Ont : Carswell, 1994.

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Chapitres de livres sur le sujet "Procedure learning"

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Goertzel, Ben, Cassio Pennachin et Nil Geisweiller. « Integrative Procedure Learning ». Dans Atlantis Thinking Machines, 369–89. Paris : Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_23.

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Falmagne, Jean-Claude, et Jean-Paul Doignon. « A Markov Chain Procedure ». Dans Learning Spaces, 273–96. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-01039-2_14.

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Goertzel, Ben, Cassio Pennachin et Nil Geisweiller. « Procedure Learning as Program Learning ». Dans Atlantis Thinking Machines, 213–16. Paris : Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_12.

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Hammer, Patrick, et Tony Lofthouse. « Goal-Directed Procedure Learning ». Dans Artificial General Intelligence, 77–86. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97676-1_8.

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Goertzel, Ben, Cassio Pennachin et Nil Geisweiller. « Probabilistic Evolutionary Procedure Learning ». Dans Atlantis Thinking Machines, 239–71. Paris : Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_15.

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Scheffer, Thomas, Kati Hannken-Illjes et Alexander Kozin. « Procedural Presence : Failing and Learning ». Dans Criminal Defence and Procedure, 117–37. London : Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230283114_5.

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Falmagne, Jean-Claude, et Jean-Paul Doignon. « Uncovering the Latent State : A Continuous Markov Procedure ». Dans Learning Spaces, 241–72. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-01039-2_13.

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Ammon, Kurt. « Some experiments with a learning procedure ». Dans Analogical and Inductive Inference, 87–98. Berlin, Heidelberg : Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-56004-1_6.

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Goertzel, Ben, Cassio Pennachin et Nil Geisweiller. « Procedure Learning via Adaptively Biased Hillclimbing ». Dans Atlantis Thinking Machines, 227–38. Paris : Atlantis Press, 2014. http://dx.doi.org/10.2991/978-94-6239-030-0_14.

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Salomon, R. « Collective Learning as an Efficient Learning and Function Optimization Procedure ». Dans Intelligent Systems Third Golden West International Conference, 77–83. Dordrecht : Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-7108-3_10.

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Actes de conférences sur le sujet "Procedure learning"

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Chang, Chen-Huei, Chao-Chih Chang et Shu-Yuen Hwang. « Connectionist learning procedure for edge detector ». Dans Robotics - DL tentative, sous la direction de David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.57061.

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Jagamogan, Reevan Seelen, Saiful Adli Ismail, Noor Hafizah Hassan et Hafiza Abas. « Penetration Testing Procedure using Machine Learning ». Dans 2022 4th International Conference on Smart Sensors and Application (ICSSA). IEEE, 2022. http://dx.doi.org/10.1109/icssa54161.2022.9870951.

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Jacobs, Gilles, et Pierre Henneaux. « Unsupervised learning procedure for NILM applications ». Dans 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON). IEEE, 2020. http://dx.doi.org/10.1109/melecon48756.2020.9140477.

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Li, Lingfeng, Richard A. Paris, Conner Pinson, Yan Wang, Joseph Coco, Jamison Heard, Julie A. Adams, Daniel V. Fabbri et Bobby Bodenheimer. « Emergency Clinical Procedure Detection With Deep Learning ». Dans 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society. IEEE, 2020. http://dx.doi.org/10.1109/embc44109.2020.9175575.

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Shiina, Hiromitsu, Akiyoshi Takahashi, Ryunosuke Ito et Nobuyuki Kobayashi. « Comment Generation System for Program Procedure Learning ». Dans 2018 7th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2018. http://dx.doi.org/10.1109/iiai-aai.2018.00018.

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Elhamifar, Ehsan, et Zwe Naing. « Unsupervised Procedure Learning via Joint Dynamic Summarization ». Dans 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00644.

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Chang, Chingwei, Kwoting Fang et Chiungyu Huang. « Dynamic Knowledge Management Procedure Using Fuzzy Clustering ». Dans 2008 Seventh International Conference on Machine Learning and Applications. IEEE, 2008. http://dx.doi.org/10.1109/icmla.2008.99.

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Abas, Marcel, et Tomas Skripcak. « A modification of gradient policy in reinforcement learning procedure ». Dans 2012 15th International Conference on Interactive Collaborative Learning (ICL). IEEE, 2012. http://dx.doi.org/10.1109/icl.2012.6402200.

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Lei, Jun, Guohui Li, Jun Zhang, Dan Lu et Qiang Guo. « Online structural SVM learning by dual ascending procedure ». Dans 2014 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2014. http://dx.doi.org/10.1109/spac.2014.6982687.

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Zhohov, Roman, Alexandros Palaios, Henrik Ryden, Reza Moosavi et Joel Berglund. « Reducing Latency : Improving Handover Procedure Using Machine Learning ». Dans 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE, 2021. http://dx.doi.org/10.1109/vtc2021-spring51267.2021.9448875.

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Rapports d'organisations sur le sujet "Procedure learning"

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Goetsch, Gordon J. CONSENSUS : A Statistical Learning Procedure in a Connectionist Network. Fort Belvoir, VA : Defense Technical Information Center, décembre 1987. http://dx.doi.org/10.21236/ada188531.

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Dafny, Leemore. Entry Deterrence in Hospital Procedure Markets : A Simple Model of Learning-By-Doing. Cambridge, MA : National Bureau of Economic Research, juillet 2003. http://dx.doi.org/10.3386/w9871.

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Wells, Rosalie, et Joseph D. Hagman. Training Procedures for Enhancing Reserve Component Learning, Retention, and Transfer. Fort Belvoir, VA : Defense Technical Information Center, septembre 1989. http://dx.doi.org/10.21236/ada217450.

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Ohlsson, Stellan. The Cognitive Function of Theoretical Knowledge in Procedural Learning. Fort Belvoir, VA : Defense Technical Information Center, mars 1992. http://dx.doi.org/10.21236/ada248075.

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Downard, Alicia, Stephen Semmens et Bryant Robbins. Automated characterization of ridge-swale patterns along the Mississippi River. Engineer Research and Development Center (U.S.), avril 2021. http://dx.doi.org/10.21079/11681/40439.

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The orientation of constructed levee embankments relative to alluvial swales is a useful measure for identifying regions susceptible to backward erosion piping (BEP). This research was conducted to create an automated, efficient process to classify patterns and orientations of swales within the Lower Mississippi Valley (LMV) to support levee risk assessments. Two machine learning algorithms are used to train the classification models: a convolutional neural network and a U-net. The resulting workflow can identify linear topographic features but is unable to reliably differentiate swales from other features, such as the levee structure and riverbanks. Further tuning of training data or manual identification of regions of interest could yield significantly better results. The workflow also provides an orientation to each linear feature to support subsequent analyses of position relative to levee alignments. While the individual models fall short of immediate applicability, the procedure provides a feasible, automated scheme to assist in swale classification and characterization within mature alluvial valley systems similar to LMV.
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Ohlsson, Stellan, et Ernest Reese. An Information Processing Analysis of the Function of Conceptual Understanding in the Learning of Arithmetic Procedures. Fort Belvoir, VA : Defense Technical Information Center, août 1988. http://dx.doi.org/10.21236/ada202740.

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Pinchuk, Olga P., Oleksandra M. Sokolyuk, Oleksandr Yu Burov et Mariya P. Shyshkina. Digital transformation of learning environment : aspect of cognitive activity of students. [б. в.], septembre 2019. http://dx.doi.org/10.31812/123456789/3243.

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Peculiar features of digital environment include: integration of ICTs; use of local and global networks and resources; support and development of qualitatively new technologies of information processing; active use of modern means, methods and forms of teaching in the educational process. The organization of activities in terms of digital learning environment provides appropriate changes in the interaction between subjects of the educational process. Today, means and technologies of the information and communication networks (ICNs), in particular the Internet, which custom and operational-procedural properties were changed at the initial stage from closed local to open ones at present, become widespread. The development of ICNs (from closed local to open ones) changes the typology of learning environments. The following models of learning environments, which widely use ICT and ICN tools (with basic features that characterize them) are distinguished: using the local communication network for presentation of educational information; using the local communication network and open network resources; using open network resources; for independent use of open network resources directly in the classroom by a student; for use of open network resources by a student in the process of independent learning activity; for use by a student educational resources, specially created by a teacher, as well as resources of an open networks in his independent learning activity.
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Hefetz, Abraham, et Justin O. Schmidt. Use of Bee-Borne Attractants for Pollination of Nonrewarding Flowers : Model System of Male-Sterile Tomato Flowers. United States Department of Agriculture, octobre 2003. http://dx.doi.org/10.32747/2003.7586462.bard.

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The use of bee natural product for enhancing pollination is especially valuable in problematic crops that are generally avoided by bees. In the present research we attempted to enhance bee visitation to Male Sterile (M-S) tomato flowers generally used in the production of hybrid seeds. These flowers that lack both pollen and nectar are unattractive to bees that learn rapidly to avoid them. The specific objects were to elucidate the chemical composition of the exocrine products of two bumble bee species the North American Bombus impatiens and the Israeli B. terrestris. Of these, to isolate and identify a bee attractant which when sprayed on M-S tomato flowers will enhance bee visitation, and to provide a procedure of the pheromone application regime. During the research we realized that our knowledge of B. impatiens is too little and we narrowed the objective to learning the basic social behavior of the bees and the pattern of foraging in a flight chamber and how it is affected by biogenic amines. Colonies of B. impatiens are characterized by a high number of workers and a relatively small number of queens. Size differences between queens and workers are pronounced and the queen seems to have full control over egg laying. Only about 9% of the workers in mature colonies had mature oocytes, and there were no signs of a "competition phase" as we know in B. terrestris. Queens and workers differ in their exocrine bouquet. Queen's Dufour's gland possesses a series of linear, saturated and unsaturated hydrocarbons whereas that of workers contains in addition a series of wax-type esters. Bees were trained to either visit or avoid artificially scented electronic flowers in a flight chamber. Since bee also learned to avoid scented non-rewarding flowers we attempted to interfere with this learning. We tested the effect of octopamine, a biogenic amine affecting bee behavior, on the choice behavior of free-flying bumblebees. Our results show that octopamine had no significant effect on the bees' equilibrium choice or on the overall rate of the behavioral change in response to the change in reward. Rather, octopamine significantly affected the time interval between the change in reward status and the initiation of behavioral change in the bee. In B. terrestris we studied the foraging pattern of the bees on tomato flowers in a semi commercial greenhouse in Yad Mordechai. Bee learned very quickly to avoid the non- rewarding M-S flowers, irrespective of their arrangement in the plot, i.e., their mixing with normal, pollen bearing flowers. However, bees seem to "forget" this information during the night since the foraging pattern repeats itself the next morning. Several exocrine products were tested as visitation enhancers. Among these, tarsal gland extracts are the most attractive. The compounds identified in the tarsal gland extract are mostly linear saturated hydrocarbons with small amounts of unsaturated ones. Application was performed every second day on leaves in selected inflorescences. Bee visitation increased significantly in the treated inflorescences as compared to the control, solvent treated. Treatment of the anthers cone was more effective than on the flower petals or the surrounding leaves. Methanol proved to be a non-flower-destructive solvent. We have shown that bumble bees (B. terrestris) can be manipulated by bee-borne attractants to visit non-rewarding flowers. We have further demonstrated that the bees learning ability can be manipulated by applying exogenously octopamine. Both methods can be additively applied in enhancing pollination of desired crops. Such manipulation will be especially useful in tomato cultivation for hybrid seed production.
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Huang, Haohang, Erol Tutumluer, Jiayi Luo, Kelin Ding, Issam Qamhia et John Hart. 3D Image Analysis Using Deep Learning for Size and Shape Characterization of Stockpile Riprap Aggregates—Phase 2. Illinois Center for Transportation, septembre 2022. http://dx.doi.org/10.36501/0197-9191/22-017.

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Riprap rock and aggregates are extensively used in structural, transportation, geotechnical, and hydraulic engineering applications. Field determination of morphological properties of aggregates such as size and shape can greatly facilitate the quality assurance/quality control (QA/QC) process for proper aggregate material selection and engineering use. Many aggregate imaging approaches have been developed to characterize the size and morphology of individual aggregates by computer vision. However, 3D field characterization of aggregate particle morphology is challenging both during the quarry production process and at construction sites, particularly for aggregates in stockpile form. This research study presents a 3D reconstruction-segmentation-completion approach based on deep learning techniques by combining three developed research components: field 3D reconstruction procedures, 3D stockpile instance segmentation, and 3D shape completion. The approach was designed to reconstruct aggregate stockpiles from multi-view images, segment the stockpile into individual instances, and predict the unseen side of each instance (particle) based on the partial visible shapes. Based on the dataset constructed from individual aggregate models, a state-of-the-art 3D instance segmentation network and a 3D shape completion network were implemented and trained, respectively. The application of the integrated approach was demonstrated on re-engineered stockpiles and field stockpiles. The validation of results using ground-truth measurements showed satisfactory algorithm performance in capturing and predicting the unseen sides of aggregates. The algorithms are integrated into a software application with a user-friendly graphical user interface. Based on the findings of this study, this stockpile aggregate analysis approach is envisioned to provide efficient field evaluation of aggregate stockpiles by offering convenient and reliable solutions for on-site QA/QC tasks of riprap rock and aggregate stockpiles.
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Kirichek, Galina, Vladyslav Harkusha, Artur Timenko et Nataliia Kulykovska. System for detecting network anomalies using a hybrid of an uncontrolled and controlled neural network. [б. в.], février 2020. http://dx.doi.org/10.31812/123456789/3743.

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In this article realization method of attacks and anomalies detection with the use of training of ordinary and attacking packages, respectively. The method that was used to teach an attack on is a combination of an uncontrollable and controlled neural network. In an uncontrolled network, attacks are classified in smaller categories, taking into account their features and using the self- organized map. To manage clusters, a neural network based on back-propagation method used. We use PyBrain as the main framework for designing, developing and learning perceptron data. This framework has a sufficient number of solutions and algorithms for training, designing and testing various types of neural networks. Software architecture is presented using a procedural-object approach. Because there is no need to save intermediate result of the program (after learning entire perceptron is stored in the file), all the progress of learning is stored in the normal files on hard disk.
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