Relevant bibliographies by topics / Efficiency of the learning process

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Efficiency of the learning process'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Efficiency of the learning process"

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Seijo, Sandra, Inés del Campo, Javier Echanobe, and Javier García-Sedano. "Electric Efficiency Modelling of a Complex Cogeneration Process Using Extreme Learning Machines." International Journal of Machine Learning and Computing 5, no. 5 (2015): 399–403. http://dx.doi.org/10.7763/ijmlc.2015.v5.541.

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Burger Pagnussat, Millana, Eduardo Silva Lopes, and Rachael D. Seidler. "Behavioural profile effect of forestry machine operators in the learning process." Journal of Forest Science 65, No. 4 (2019): 144–49. http://dx.doi.org/10.17221/27/2019-jfs.

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A lack of efficient operators for wood harvesting machines poses a great challenge. Here, our objective was to evaluate the effect of the behavioural profile on the productive efficiency of forwarder operators. The study was carried out in a Brazilian company, with a sample of 10 operators. A profile evaluation characterized the reference profile, comparing with the profile of the operators studied. The operators were evaluated through their productive efficiency, for 11 months to track learning curves. The results showed that operators must be attentive to details, deadlines, rules, be patien
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HAYRAPETYAN, Lusine. "Art-technologies as innovative approaches in the learning process." Scientific Bulletin of Flight Academy. Section: Pedagogical Sciences 10 (2021): 102–6. http://dx.doi.org/10.33251/2522-1477-2021-10-102-106.

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Pedagogical art technologies and methods to increase the efficiency of the teaching process are considered as innovative approaches to the pedagogical process. Within the framework of the article, new approaches to make the pedagogical process more creative were revealed, due to which a number of problems of pedagogical nature can be solved, including the organization of the process of teaching, socialization, upbringing, etc. Aim of the article: The aim of the research conducted within the framework of the article is to identify the importance of involving art technologies and methods in incr
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Yusufova, Madinakhan, and Sevara Jumanova. "EFFICIENCY OF COOPERATIVE LANGUAGE LEARNING." JOURNAL OF UNIVERSAL SCIENCE RESEARCH 1, no. 5 (2023): 77–82. https://doi.org/10.5281/zenodo.7886126.

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Cooperative language learning is an instructional method that give a chance for students to exchange different learning skills and techniques, learn from each other.The paper shows that the concept of cooperative language learning,that effectively used in the process of learning language and it can provide students with necessary  social and academic skills.
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Mergenthaler, Wolfgang, Daniel Jaroszewski, Salah-Eddine Morsili, and Benedikt Sturm. "Machine Learning Can Maximize Efficiency in an Industrial Process." International Journal of Industrial Engineering 8, no. 1 (2021): 14–20. http://dx.doi.org/10.14445/23499362/ijie-v8i1p103.

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Shavkatovich, Rakhmonov Mirzokhid. "INCREASING LESSON EFFICIENCY WITH THE USE OF DIGITAL TECHNOLOGIES IN THE EDUCATIONAL PROCESS." International Journal of Pedagogics 03, no. 05 (2023): 157–60. http://dx.doi.org/10.37547/ijp/volume03issue05-30.

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Vlasov, D. V. "The factors of efficiency of distance learning." Izvestiya MGTU MAMI 8, no. 3-5 (2014): 153–57. http://dx.doi.org/10.17816/2074-0530-67505.

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The article discusses the role of a tutor (learning process organizer) in distance learning system, as well as the requirements for modern and efficient systems of e-learning. It was found that personal qualities of a tutor significantly affect the efficiency of the educational process, even in distance forms of education.
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Volkova, Liudmyla. "COMMUNICATIVE ASPECT OF FOREIGN LANGUAGE LEARNING PROCESS." Naukovì zapiski Nacìonalʹnogo unìversitetu «Ostrozʹka akademìâ». Serìâ «Fìlologìâ» 1, no. 12(80) (2021): 163–65. http://dx.doi.org/10.25264/2519-2558-2021-12(80)-163-165.

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The importance of forming foreign language communicative competence in the context of professional training has been ascertained for efficient usage in learning process of foreign language. The efficiency of communicative aspect in the educational process of higher education is proved, as it provide an opportunity to form professional skills of future professionals, involving them in intensive cognitive, intellectual and creative activity. Communicative activity is considered as a process of solving a number of professional tasks by students. This activity is aimed at achieving a common goal –
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Lamanauskas, Vincentas, Violeta Šlekienė, Loreta Ragulienė, and Renata Bilbokaitė. "DIGITAL TEACHING/LEARNING CONTENT IN NATURAL SCIENCE EDUCATION PROCESS: EFFICIENCY EVALUATION." GAMTAMOKSLINIS UGDYMAS / NATURAL SCIENCE EDUCATION 8, no. 2 (2011): 8–26. http://dx.doi.org/10.48127/gu-nse/11.8.08a.

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Over the latter years education practice has changed a lot. New ways, forms and means of teaching “are coming” to comprehensive schools. Even applying common teaching methods and forms, their application algorithm is changing. First of all, it is related to virtual environment. You can find plenty of important material for education practice in the internet. One of urgent fields is digital teaching/learning content. We can basically assert that digital teaching/learning content is a perspective way seeking to improve education process. However, it is not right to refer only to research works c
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Shoenbill, Kimberly, Yiqiang Song, Nichelle L. Cobb, Marc K. Drezner, and Eneida A. Mendonca. "IRB Process Improvements: A Machine Learning Analysis." Journal of Clinical and Translational Science 1, no. 3 (2017): 176–83. http://dx.doi.org/10.1017/cts.2016.25.

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ObjectiveClinical research involving humans is critically important, but it is a lengthy and expensive process. Most studies require institutional review board (IRB) approval. Our objective is to identify predictors of delays or accelerations in the IRB review process and apply this knowledge to inform process change in an effort to improve IRB efficiency, transparency, consistency and communication.MethodsWe analyzed timelines of protocol submissions to determine protocol or IRB characteristics associated with different processing times. Our evaluation included single variable analysis to ide
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Dissertations / Theses on the topic "Efficiency of the learning process"

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Bui, Thang Duc. "Efficient deterministic approximate Bayesian inference for Gaussian process models." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/273833.

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Gaussian processes are powerful nonparametric distributions over continuous functions that have become a standard tool in modern probabilistic machine learning. However, the applicability of Gaussian processes in the large-data regime and in hierarchical probabilistic models is severely limited by analytic and computational intractabilities. It is, therefore, important to develop practical approximate inference and learning algorithms that can address these challenges. To this end, this dissertation provides a comprehensive and unifying perspective of pseudo-point based deterministic approxima
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Snelson, Edward Lloyd. "Flexible and efficient Gaussian process models for machine learning." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1445855/.

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Gaussian process (GP) models are widely used to perform Bayesian nonlinear regression and classification tasks that are central to many machine learning problems. A GP is nonparametric, meaning that the complexity of the model grows as more data points are received. Another attractive feature is the behaviour of the error bars. They naturally grow in regions away from training data where we have high uncertainty about the interpolating function. In their standard form GPs have several limitations, which can be divided into two broad categories: computational difficulties for large data sets, a
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Ikeuchi, Daiki. "Data-efficient Machine Learning for Geometry Modelling in Cold Spray Additive Manufacturing." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23253.

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Additive manufacturing (AM) is widely recognised as a paradigm shift in the nature of future manufacturing as it has demonstrated the potential to offer the variety of benefits that are difficult to achieve otherwise, including: mass-customisation, great freedom of design, waste minimisation and the ability to fabricate complex shapes. However, the commercial integration of AM technologies is still greatly limited, especially High Production Rate AM (HPRAM) technology in metal AM domains. Such limitation is attributed to the lack of process monitoring and quality assurance measures in metal AM
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Guss, Herman, and Linus Rustas. "Applying Machine Learning Algorithms for Anomaly Detection in Electricity Data : Improving the Energy Efficiency of Residential Buildings." Thesis, Uppsala universitet, Byggteknik och byggd miljö, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-415507.

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The purpose of this thesis is to investigate how data from a residential property owner can be utilized to enable better energy management for their building stock. Specifically, this is done through the development of two machine learning models with the objective of detecting anomalies in the existing data of electricity consumption. The dataset consists of two years of residential electricity consumption for 193 substations belonging to the residential property owner Uppsalahem. The first of the developed models uses the K-means method to cluster substations with similar consumption pattern
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Долгова, Наталія Олександрівна, Наталия Александровна Долгова, and Nataliia Oleksandrivna Dolgova. "The efficiency of e-learning program in a process of professional training specialists of physical education and sport in the EU countries." Thesis, Sumy State Uiversity, 2016. http://essuir.sumdu.edu.ua/handle/123456789/48267.

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The current education system includes various forms of information technologies which are used in educational process in higher education institutions. In European countries the declared priority is an entry of all EU countries’ education and training systems to the Lisbon Declaration, which supports the general trend of informatization of education.
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Fakih, Saif. "A learning approach to obtain efficient testing strategies in medical diagnosis." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000309.

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Бушуева, К. С., та K. S. Bushueva. "Внедрение машинного обучения в системы электронного документооборота : магистерская диссертация". Master's thesis, б. и, 2020. http://hdl.handle.net/10995/93436.

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Актуальность выбранной темы состоит в том, что внедрение машинного обучения в системы электронного документооборота является новым и мощным инструментом для упрощения работы с документами. Многие организации уже перевели бумажный документооборот в электронный, поэтому необходимо рассмотреть вопрос как внедрение машинного обучения с систему электронного документооборота повысит производительность каждого сотрудника и предприятия в целом. Целью исследования является автоматизация процесса подготовки документа с использованием алгоритмов машинного обучения. Материалы данной работы, обобщённые по
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Kohring, Bajo. "Övning : Strategier, resurser och effektivitet ur ett designteoretiskt perspektiv." Thesis, Karlstads universitet, Institutionen för konstnärliga studier, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-41147.

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Detta arbete syftar till att utforska hur övning på fiol kan designas för att den ska kännas meningsfull och effektiv. Studiens forskningsfråga är: Vilka semiotiska resurser använder jag mig av när jag övar terser på fiol? För att undersöka detta har jag under ett år gjort tekniska övningar med hjälp av olika övningsstrategier för att se progressionen i min utvecklingsprocess. Studiens metod är videoobservation och loggboksskrivande och arbetet utgår från ett designteoretiskt perspektiv. Resultatet presenteras i två teman: Semiotiska resurser för dokumentation och Semiotiska resurser för motiv
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Souza, Iberê Guarani de. "Os programas de melhoria realmente importam?: uma avaliação em uma empresa de manufatura." Universidade do Vale do Rio dos Sinos, 2014. http://www.repositorio.jesuita.org.br/handle/UNISINOS/4456.

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Submitted by Maicon Juliano Schmidt (maicons) on 2015-07-15T14:12:15Z No. of bitstreams: 1 Iberê Guarani de Souza.pdf: 3328129 bytes, checksum: 6f2250512f214402473b148d4ad6e48d (MD5)<br>Made available in DSpace on 2015-07-15T14:12:15Z (GMT). No. of bitstreams: 1 Iberê Guarani de Souza.pdf: 3328129 bytes, checksum: 6f2250512f214402473b148d4ad6e48d (MD5) Previous issue date: 2014-01-31<br>Nenhuma<br>As empresas buscam, a cada dia, melhorar sua eficiência produtiva e, com isso, aumentar sua lucratividade e competitividade. Para tanto, há diversas formas de descobrir os fatores críticos de c
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Najibullah, Khan Nazreen Begum. "Process Efficiency Optimisation of Cascade LNG Process." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/75842.

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The aimed of this thesis is to optimise the Cascade LNG process efficiency of 5 MTPA production capacity. The cascade process was modelled and simulated in Aspen HYSYS version 7.2 using Peng Robinson equation of state. The optimisation of cascade process was carried out from operation and design perspectives. It focused on two main cycles which are propane and ethylene refrigeration cycles as they are the main energy consumers of this process.
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Books on the topic "Efficiency of the learning process"

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Senge, Peter M. The fifth discipline: The art and practice of the learning organization. Doubleday/Currency, 1990.

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Pilavachi, P. A., ed. Energy Efficiency in Process Technology. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1454-7.

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Federighi, Paolo, and Francesca Torlone, eds. Low skilled take their qualifications "one step up". Firenze University Press, 2010. http://dx.doi.org/10.36253/978-88-6453-179-3.

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Adult learning is recognized as a key component of lifelong learning and Member States are required to remove barriers to participation, to increase overall quality and efficiency in adult learning, to speed up the process of validation and recognition and to ensure sufficient investment in and monitoring of the field (European Commission, 2006, 2007; European Parliament, 2008; European Council, 2008). It is unanimously recognized that adult learning can play a pivotal role in meeting the goals of the Lisbon Strategy, by fostering social cohesion, providing citizens with the skills required to
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Great Britain. Central Office of Information. and Great Britain. Energy Efficiency Office., eds. Process plant insulation and fuel efficiency. Energy Efficiency Office, 1986.

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Great Britain. Energy Efficiency Office., ed. Process plant insulation and fuel efficiency. Energy Efficiency Office, 1994.

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Biggs, John B. Process of learning. 3rd ed. Prentice-Hall of Australia, 1993.

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Gupta, Rajinder M., and Peter Coxhead, eds. Cultural Diversity and Learning Efficiency. Palgrave Macmillan UK, 1988. http://dx.doi.org/10.1007/978-1-349-19131-4.

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Gopalakrishnan, B. Energy efficiency in industrial process heating systems. Knovel, 2009.

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Dixon, Valerie. Learning competency architecture: 6Cs learning process. Learnware Design, 2008.

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Marian, McCabe, Lewis Richard, and Togher Family Centre, eds. Lifelong learning: "The process". Togher Family Centre, 1998.

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Book chapters on the topic "Efficiency of the learning process"

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Walther, Christian, Frank Beneke, Luise Merbach, Hubertus Siebald, Oliver Hensel, and Jochen Huster. "Machine-specific Approach for Automatic Classification of Cutting Process Efficiency." In Machine Learning for Cyber Physical Systems. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-48838-6_12.

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Frey, Christian M. M., Simon Rauch, Oliver Stritzel, and Moike Buck. "Process-aware Learning." In Unlocking Artificial Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_6.

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AbstractProcesses in companies are diverse and complex. The production of different products, inter- or intra-company logistic processes, or other serial event sequences within companies have one thing in common: they can be traced on the basis of a documentation of the individual process steps. Usually, companies have domain experts for each department’s processes who use their experience and knowledge to plan and control these steps. However, with increasing complexity and diversity of processes, efficient planning and control is becoming more difficult or even impossible for human decision
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González, Inés, Enric Serradell, and David Castillo. "An Approach to the Relationship between Efficiency and Process Management." In Information Systems, E-learning, and Knowledge Management Research. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35879-1_8.

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Nayak, Manjushree, and Subhakanta Panda. "Machine Learning for Nano Process Optimization: Enhancing Efficiency in Nanofabrication." In Information Systems Engineering and Management. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-77296-2_3.

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Tao, Jun, Wangyang Zhang, Xin Li, et al. "Efficient Process Variation Characterization by Virtual Probe." In Machine Learning in VLSI Computer-Aided Design. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04666-8_7.

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Saedon, J. B., M. F. Othman, N. H. Mohamad Nor, M. S. Mohd Syawal, M. S. Meon, and Muhammad Razin Raghazli. "Enhancing WEDM Efficiency by Teaching–Learning-Based Optimization for Machining Process Parameter Optimization." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-8819-8_44.

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Redis, Andrei Cosmin, Mohammadreza Fani Sani, Bahram Zarrin, and Andrea Burattin. "Skill Learning Using Process Mining for Large Language Model Plan Generation." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82225-4_48.

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Abstract Large language models (LLMs) hold promise for generating plans for complex tasks, but their effectiveness is limited by sequential execution, lack of control flow models, and difficulties in skill retrieval. Addressing these issues is crucial for improving the efficiency and interpretability of plan generation as LLMs become more central to automation and decision-making. We introduce a novel approach to skill learning in LLMs by integrating process mining techniques, leveraging process discovery for skill acquisition, process models for skill storage, and conformance checking for ski
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Naushad, Mohammad, and Abdul Malik Syed. "An Investigation of Teaching and Learning Process Efficiency in a Business School Using DEA." In Explore Business, Technology Opportunities and Challenges ‎After the Covid-19 Pandemic. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08954-1_16.

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Olatunji, Sunday O., Abdulrahman S. Almuhaidib, Abdulaziz S. Alhuwaishil, et al. "Automating Compliance Evidence Extraction with Machine Learning." In Proceedings in Technology Transfer. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8588-9_3.

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Abstract This paper integrates existing literature on the subject that converges with ongoing discussions concerning cyber security and machine learning. The paper advocates for the transformative potential of automation in compliance processes, offering increased efficiency and reliability. This study explores the intersection of cybersecurity and machine learning, focusing on how machine learning can independently analyze documents to establish whether they meet the prescribed evidence standards through programmed algorithms. Cybersecurity compliance evaluations typically require stakeholder
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Folino, Francesco, Gianluigi Folino, Massimo Guarascio, and Luigi Pontieri. "Explainable Process Deviance Discovery with Data-Efficient Deep Learning." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81241-5_6.

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Conference papers on the topic "Efficiency of the learning process"

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Bloor, Maximilian, Tom Savage, Calvin Tsay, Ehecatl Antonio Del Rio Chanona, and Max Mowbray. "A Subset Selection Strategy for Gaussian Process Q-Learning of Process Optimization and Control." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.126649.

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This work addresses a practical challenge in batch process optimization: the need for sample efficient learning methods due to the high cost and time-intensive nature of running physical batch processes. While reinforcement learning (RL) offers a promising framework for optimizing batch processes, traditional approaches require numerous experimental runs to converge to optimal policies. A novel sample efficient RL method that leverages Gaussian Processes (GPs) to accelerate learning from limited batch data is proposed. However, the direct application of GPs becomes computationally intractable
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Dorneanu, Bogdan, Vasileios K. Mappas, and Harvey Arellano-Garcia. "A Novel Approach to Gradient Evaluation and Efficient Deep Learning: A Hybrid Method." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.120349.

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Deep learning faces significant challenges in efficiently training large-scale models. These issues are closely linked, as efficient training often depends on precise and computationally feasible gradient calculations. This work introduces innovative methodologies to improve deep learning network (DLN) training in complex systems. A novel approach to DLN training is proposed by adapting the block coordinate descent (BCD) method, which optimizes individual layers sequentially. This is combined with traditional batch-based training to create a hybrid method that harnesses the strengths of both t
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Braniff, Austin, Fengqi You, and Yuhe Tian. "Enhanced Reinforcement Learning-driven Process Design via Quantum Machine Learning." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.149501.

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In this work, we introduce a quantum-enhanced reinforcement learning (RL) framework for process design synthesis. RL-driven methods for generating process designs have gained momentum due to their ability to intelligently identify optimal configurations without requiring pre-defined superstructures or flowsheet configurations. This eliminates reliance on prior expert knowledge, offering a comprehensive and robust design strategy. However, navigating the vast combinatorial design space poses computational challenges. To address this, a novel approach integrating RL with quantum machine learning
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Paranjpe, Nikhil, Shruti Kshirsagar, and Ramazan Asmatulu. "Integrating Machine Learning Models to Enhance the Efficiency of a Desalination Process." In 2025 IEEE Green Technologies Conference (GreenTech). IEEE, 2025. https://doi.org/10.1109/greentech62170.2025.10977633.

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Queiroz, Luana P., Olve R. Bruaset, Ana M. Ribeiro, and Idelfonso B. R. Nogueira. "Optimization of Shell and Tube Heat Exchangers Using Reinforcement Learning." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.192011.

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This work presents a model for optimizing shell-and-tube heat exchanger design using Q-learning, a reinforcement learning technique. An agent is trained to interact with a simulated environment of a heat exchange model, iteratively refining design configurations to maximize a reward function. This reward function balances heat exchanger effectiveness and pressure drop, emphasizing designs that minimize pressure drop. Results showed that simpler configurations consistently achieved higher rewards, despite complex designs offering better heat transfer efficiency.
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Yu, Songhyun, Sangho Yoon, Sungjin Lim, et al. "Semiconductor image analysis using data-efficient machine learning." In Metrology, Inspection, and Process Control XXXIX, edited by Matthew J. Sendelbach and Nivea G. Schuch. SPIE, 2025. https://doi.org/10.1117/12.3050624.

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Mahmood, Farhat, Sarah Namany, and Rajesh Govindan. "Data-Driven Reinforcement Learning for Greenhouse Temperature Control." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.189272.

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Efficient temperature control in greenhouses is essential for optimal plant growth, especially in arid regions where the harsh environment poses significant challenges to maintaining a stable microclimate. Maintaining the optimum temperature range directly influences healthy plant development and overall agricultural productivity, impacting crop yields and financial outcomes. However, the greenhouse in the present case study fails to maintain the optimum temperature as it operates based on predefined settings, limiting its ability to adapt to dynamic climate conditions. To maintain an ideal te
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Iqbal, Imam M., Xinyu Wang, Isabell Viedt, and Leonhard Urbas. "Leveraging Machine Learning for Real-Time Performance Prediction of Near Infrared Separators in Waste Sorting Plant." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.130911.

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Many small and medium enterprises (SME) often fail to fully utilize the data they collect due to a lack of technical expertise. The ecoKI platform, a low-code solution that simplifies machine learning application for SMEs, showed a promising answer to the challenge. This study explores the application of ecoKI platform to design process monitoring tools for waste sorting plants. NIR separator data were processed through ecoKI�s building blocks to train two neural network architectures�MLP and LSTM�for predicting NIR separation efficiency. The results showed that the models accurately predicted
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Cherif, Manar, Bechir Bouaziz, and Faouzi Bacha. "Analysis of the Weather Impact on the Photovoltaic Panel Efficiency Based on Machine Learning Techniques." In 2024 IEEE International Multi-Conference on Smart Systems & Green Process (IMC-SSGP). IEEE, 2024. https://doi.org/10.1109/imc-ssgp63352.2024.10919865.

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Territo, Kyle, Peter Vallet, and Jose Romagnoli. "Towards Self-Tuning PID Controllers: A Data-Driven, Reinforcement Learning Approach for Industrial Automation." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.132857.

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As industries embrace the digitalization of Industry 4.0, the abundance of process data creates new opportunities to optimize industrial control systems. Traditional Proportional-Integral-Derivative (PID) controllers often require manual tuning to address changing conditions. This paper introduces an automated, adaptive PID tuning method using historical data and machine learning for a continuously evolving, data-driven approach. The method centers on training a surrogate model using historical process data to replicate real system behavior under various conditions. This enables safe explorati
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Reports on the topic "Efficiency of the learning process"

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Osadchyi, Viacheslav V., Hanna Y. Chemerys, Kateryna P. Osadcha, Vladyslav S. Kruhlyk, Serhii L. Koniukhov, and Arnold E. Kiv. Conceptual model of learning based on the combined capabilities of augmented and virtual reality technologies with adaptive learning systems. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4417.

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The article is devoted to actual problem of using modern ICT tools to increase the level of efficiency of the educational process. The current state and relevance of the use of augmented reality (AR) and virtual reality (VR) technologies as an appropriate means of improving the educational process are considered. In particular, attention is paid to the potential of the combined capabilities of AR and VR technologies with adaptive learning systems. Insufficient elaboration of cross-use opportunities for achieving of efficiency of the educational process in state-of-the-art research has been ide
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Clements, Michael, Robert W. Rich, and Joseph Tracy. An Investigation into the Uncertainty Revision Process of Professional Forecasters. Federal Reserve Bank of Cleveland, 2024. http://dx.doi.org/10.26509/frbc-wp-202419.

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Following Manzan (2021), this paper examines how professional forecasters revise their fixed-event uncertainty (variance) forecasts and tests the Bayesian learning prediction that variance forecasts should decrease as the horizon shortens. We show that Manzan's (2021) use of first moment "efficiency" tests are not applicable to studying revisions of variance forecasts. Instead, we employ monotonicity tests developed by Patton and Timmermann (2012) in the first application of these tests to second moments of survey expectations. We find strong evidence that the variance forecasts are consistent
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Schellinger, Adam, Jenna Zacamy, Jeremy Roschelle, Avery Closser, and Cristina Zepeda. Considerations for Conducting Research in Digital Learning Platforms. Digital Promise, 2024. http://dx.doi.org/10.51388/20.500.12265/210.

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The five SEERNet digital learning platforms (DLPs) present unique opportunities for researchers by offering tools, processes, and infrastructure to make research more efficient, scalable, and relevant. However, conducting research within a DLP may require a shift in a researcher’s orientation or mindset in how they think about potential research questions, study samples, available data, and planning study logistics. We encourage researchers to think flexibly about how they might adapt their ideas to the specific learning platform and consider iterating toward a more comprehensive understanding
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Nakasone, Eduardo, Lorena Alcázar, and Máximo Torero. Provision of Public Services and Welfare of the Poor: Learning from an Incomplete Electricity Privatization Process in Rural Peru. Inter-American Development Bank, 2007. http://dx.doi.org/10.18235/0011287.

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The incomplete privatization of the electric sector in Peru provides a unique scenario for evaluating the impact of public versus private provision. The results in this paper suggest that management of electricity firms by the private sector leads to a significant improvement in the quality of the provision of electricity. These improvements in quality and supply of electricity provision yield some efficiency gains in terms of the time allocation of the working labor force that can be directly linked to the use of electricity. Rural households under private provision of electricity had more op
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Salter, R., Quyen Dong, Cody Coleman, et al. Data Lake Ecosystem Workflow. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40203.

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The Engineer Research and Development Center, Information Technology Laboratory’s (ERDC-ITL’s) Big Data Analytics team specializes in the analysis of large-scale datasets with capabilities across four research areas that require vast amounts of data to inform and drive analysis: large-scale data governance, deep learning and machine learning, natural language processing, and automated data labeling. Unfortunately, data transfer between government organizations is a complex and time-consuming process requiring coordination of multiple parties across multiple offices and organizations. Past succ
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Ступнік, М. І., В. С. Моркун, and З. П. Бакум. Information and Communication Technologies in the Process of Mining Engineer Training. Криворізький державний педагогічний університет, 2013. http://dx.doi.org/10.31812/0564/405.

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Based on scientific analysis the authors of the article argued the necessity of solving priority tasks – the development of new educational technologies aimed at supporting the training of engineers in terms of the mining engineering as high-tech industry. The features of mining computer technologies are determined. There was worked out the project of the adaptive system of a mining engineer individual training "Electronic manual" aimed at the development of future professionals. The essence of individual preparation of future mining engineer ICT is defined. It is proved that the efficiency of
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Bailey Bond, Robert, Pu Ren, James Fong, Hao Sun, and Jerome F. Hajjar. Physics-informed Machine Learning Framework for Seismic Fragility Analysis of Steel Structures. Northeastern University, 2024. http://dx.doi.org/10.17760/d20680141.

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The seismic assessment of structures is a critical step to increase community resilience under earthquake hazards. This research aims to develop a Physics-reinforced Machine Learning (PrML) paradigm for metamodeling of nonlinear structures under seismic hazards using artificial intelligence. Structural metamodeling, a reduced-fidelity surrogate model to a more complex structural model, enables more efficient performance-based design and analysis, optimizing structural designs and ease the computational effort for reliability fragility analysis, leading to globally efficient designs while maint
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Triakina, Olga O., Olena O. Pavlenko, Nataliia P. Volkova, and Darja Kassim. Usage of E-learning Tools in Self-education of Government Officers Involved in Global Trade Activities. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2670.

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The article concerns the issue of e-learning tools implementation, including the Customs Learning and Knowledge Community electronic platform designed by the World Customs Organization and the Trade Facilitation Implementation Guide case studies collected by the United Nations Economic Commission for Europe, into the self-education process of current government employees (within in-service training) and future public officers (within master’s programs) connected with international trade transactions. The authors give a description of the content and characteristical features of existing e-lear
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De Michele, Roberto, and Juan Cruz Vieyra. From Fishing to Catching: Developing Actionable Red Flags in Public Procurement to Prevent and Control Corruption. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004595.

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How can entities responsible for public procurement more reliably detect collusion and other irregular behavior? Most of the existing red flag tools are based on ex post analysis of public procurement data and are not integrated into national procurement systems. This does not allow them to identify irregularities in a timely manner, negatively affecting the efficiency and transparency of public spending. This document describes the red flags solution implemented in Paraguay, which contributes to solving these problems. It combines rule-based and machine learning algorithms to provide public o
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and m
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