We are proudly a Ukrainian website. Our country was attacked by Russian Armed Forces on Feb. 24, 2022.
You can support the Ukrainian Army by following the link: https://u24.gov.ua/.
Even the smallest donation is hugely appreciated!
Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями
Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Learning tracks".
Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.
Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.
Goncharov, Pavel, Egor Shchavelev, Gennady Ososkov, and Dmitriy Baranov. "BM@N Tracking with Novel Deep Learning Methods." EPJ Web of Conferences 226 (2020): 03009. http://dx.doi.org/10.1051/epjconf/202022603009.
Three deep tracking methods are presented for the BM@N experiment GEM track detector, which differ in their concepts. The first is a two-stage method with data preprocessing by a directional search in the k-d tree to find all possible candidates for tracks, and then use a deep recurrent neural network to classify them by true and ghost tracks. The second end-to-end method used a deep recurrent neural network to extrapolate the initial tracks, similar to the Kalman filter, which learns necessary parameters from the data. The third method implements our new attempt to adapt the neural graph network approach developed in the HEP.TrkX project at CERN to GEM-specific data. The results of applying these three methods to simulated events are presented.
2
Franceschini, Giordano, Mara Terzini, and Elisabetta M. Zanetti. "Learning curves of elite car racers." International Journal of Sports Science & Coaching 12, no. 2 (February 21, 2017): 245–51. http://dx.doi.org/10.1177/1747954117694929.
This work is focused on racing cars driver’s training. Nine different tracks are considered and six drivers. Each driver drives on every track and performs consecutive trial sessions on each track; each session is made of various laps, and lap times are fitted using an exponential model, yielding an estimate of the initial performance, the learning constant, and the asymptotic performance. According to results, the learning curve varies significantly among pilots and among tracks; all pilots reach their session asymptotic performance in less than nine laps. The asymptotic performance in consecutive trial sessions improves significantly, and it is strongly correlated to the initial session performance (r2 > 0.99). As a conclusion, it is more profitable to perform separated sessions made of few laps (less than 10) rather than performing a smaller number of longer sessions. Whenever the initial lap time stops decreasing systematically, trial sessions should end because the asymptotic performance is not likely to improve further.
3
Latkar, Charu. "Railway Track Monitoring System." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 15, 2021): 1403–10. http://dx.doi.org/10.22214/ijraset.2021.36134.
For the protection and proximity of railway networks it is substantial to Promptly detect and identify faults in the railway tracks. In this paper, railway track fault diagnosis is approximated from the vertical and lateral acceleration using a MPU6050. MPU6050 consisting of three sensors namely gyroscope, magnetometer and accelerometer are used to distinguish line and level as symetricities in a railway track. A GSM module is used to notify the location of faults on tracks. Arduino Microcontroller is interfaced using Arduino UNO IDE. The results show that the condition of railway track irregularity and railway track striation can be approximated constructively. The processed data is uploaded to the open source cloud provider thingspeak.com. The use of various Machine Learning Algorithms are proposed to accomplish the above tasks based on the commonly available measured signals. By considering the signals from multiple railway tracks in a geographic location, faults are diagnosed from their spatial and temporal dependencies. The irregularities in the railway tracks are detected using the Inertial Monitoring Unit, providing the necessary data about future deformities using Machine Learning. Using Python 3.0, a generative model is developed to show that the AdaBoost network can learn these dependencies directly from the data. Seven different classification algorithms used for this project are Logistic regression,Naive Bayes Algorithm,Support Vector Machine, Ensemble Machine (Average) learning Algorithm, XGBoost Classifier, Extreme Machine Learning and AdaBoost Classifier. Among the above 7 classification algorithms, AdaBoost Learning has given the highest accuracy,i.e of 93.93 %. The AdaBoost Machine Learning Model is used throughout the model.
4
Togelius, Julian, Noor Shaker, Sergey Karakovskiy, and Georgios N. Yannakakis. "The Mario AI Championship 2009-2012." AI Magazine 34, no. 3 (September 15, 2013): 89–92. http://dx.doi.org/10.1609/aimag.v34i3.2492.
We give a brief overview of the Mario AI Championship, a series of competitions based on an open source clone of the seminal platform game Super Mario Bros. The competition has four tracks. The gameplay and learning tracks resemble traditional reinforcement learning competitions, the Level generation track focuses on the generation of entertaining game levels, and the Turing Test track focuses on humanlike game-playing behavior. We also outline some lessons learned from the competition and its future. The article is written by the four organizers of the competition.
5
Daher, Wajeeh. "Wiki Interaction Tracks in Geometry Learning." International Journal of E-Adoption 2, no. 4 (October 2010): 15–34. http://dx.doi.org/10.4018/jea.2010100102.
The constant comparative method (Lincoln & Guba, 1985) was used to analyze preservice teachers’ discussions and interactions in wiki discussion sections regarding geometric lessons that were written by other preservice teachers in the year before. The data was compared for the following interaction aspects of knowledge building: dialogical actions, participants’ roles, and discussion tracks. Research shows that building their content and pedagogic content knowledge, the preservice teachers together with the lecturer used mainly proposing, asking, requesting, arguing, presenting, and moving the discussion forward as dialogical actions. Proposing and asking were used for various goals such as proposing various ideas and actions, and asking about different issues concerned with geometric content and pedagogic content knowledge. The lecturer asked questions more than the preservice teachers, while the preservice teachers proposed more than the lecturer. The knowledge building was collaborative in nature, and one important aspect which enabled the collaboration is the topology of the wiki discussion section. This topology enables presenting the content of the messages; not just the titles, where the contents are presented as having the same level and thus the same importance.
6
Zhang, Yao, Ye Yuan, and Qiumei Ma. "BESIII Drift Chamber Tracking with Machine Learning." EPJ Web of Conferences 245 (2020): 02033. http://dx.doi.org/10.1051/epjconf/202024502033.
The tracking efficiency and the quality for the drift chamber of the BESIII experiment is essential to the physics analysis. The tracking efficiency of the drift chamber of BESIII is high for the high momentum tracks but still have room to improve for the low momentum tracks, especially for the tracks with multiple turn. A novel way to use a convolutional network called U-Net network is represented to solve the identification of the first turn’s hits for the multiple-turn tracks.
7
Jin, Cong, Tao Wang, Shouxun Liu, Yun Tie, Jianguang Li, Xiaobing Li, and Simon Lui. "A Transformer-Based Model for Multi-Track Music Generation." International Journal of Multimedia Data Engineering and Management 11, no. 3 (July 2020): 36–54. http://dx.doi.org/10.4018/ijmdem.2020070103.
Most of the current works are still limited to dealing with the melody generation containing pitch, rhythm, duration of each note, and pause between notes. This paper proposes a transformer-based model to generate multi-track music including tracks of piano, guitar, and drum, which is abbreviated as MTMG model. The proposed MTMG model is mainly innovated and improved on the basis of transformer. Firstly, the model obtains three target sequences after pairwise learning through learning network. Then, according to these three target sequences, GPT is applied to predict and generate three closely related sequences of instrument tracks. Finally, the three generated instrument tracks are fused to obtain multi-track music pieces containing piano, guitar, and drum. To verify the effectiveness of the proposed model, related experiments are conducted on a pair of comparative subjective and objective evaluation. The encouraging performance of the proposed model over other state-of-the-art models demonstrates its superiority in musical representation.
8
Schmidt, James R., and Jan De Houwer. "Contingency Learning Tracks With Stimulus-Response Proportion." Experimental Psychology 63, no. 2 (March 2016): 79–88. http://dx.doi.org/10.1027/1618-3169/a000313.
Abstract. We investigate the processes involved in human contingency learning using the color-word contingency learning paradigm. In this task, participants respond to the print color of neutral words. Each word is frequently presented in one color. Results show that participants respond faster and more accurately to words presented in their expected color. In Experiment 1, we observed better performance for high- relative to medium-frequency word-color pairs, and for medium- relative to low-frequency pairs. Within the medium-frequency condition, it did not matter whether the word was predictive of a currently-unpresented color, or the color was predictive of a currently-unpresented word. We conclude that a given word facilitates each potential response proportional to how often they co-occurred. In contrast, there was no evidence for costs associated with violations of high-frequency expectancies. Experiment 2 further introduced a novel word baseline condition, which also provided no evidence for competition between retrieved responses.
9
Gadson, Mark, Deanne Repetto, and Sherri L. Wallace. "2008 APSA Teaching and Learning Track Summaries—Track Six: Simulations and Role Play II." PS: Political Science & Politics 41, no. 03 (June 18, 2008): 618–20. http://dx.doi.org/10.1017/s1049096508270897.
The 2008 Simulations and Role Play (S&RP) II track focused on issues in American politics and theory. Building on conversations in previous tracks (see S&RP track summaries from 2006 and 2007 inPS), the 25 discussants focused the dialogue mainly on best practices with some discussion on faculty research.
10
Kapoor, Rajiv, Rohini Goel, and Avinash Sharma. "Deep Learning Based Object and Railway Track Recognition Using Train Mounted Thermal Imaging System." Journal of Computational and Theoretical Nanoscience 17, no. 11 (November 1, 2020): 5062–71. http://dx.doi.org/10.1166/jctn.2020.9342.
An intelligent railways safety system is very essential to avoid the accidents. The motivation behind the problem is the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. Continuous research is being carried out by distinct researchers to ensure railway safety and to reduce accident rates. In this paper, a novel method is proposed for identifying objects (obstacles) on the railway tracks in front of a moving train using a thermal camera. This approach presents a novel way of detecting the railway tracks as well as a deep network based method to recognize obstacles on the track. A pre-trained network is used that provides the model understanding of real world objects and enables deep learning classifiers for obstacle identification. The validation data is acquired by thermal imaging using night vision IR camera. In this work, the Faster R-CNN is used that efficiently recognize obstacles on the railway tracks. This process can be a great help for railways to reduce accidents and financial burdens. The result shows that the proposed method has good accuracy of approximately 83% which helps to enhance the railway safety.
Tang, Fung Michael, and 鄧峰. "Sequence classification and melody tracks selection." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B29742973.
Tang, Fung Michael. "Sequence classification and melody tracks selection /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B25017470.
Unger, Mary Ann. "Traversing the tracks : students with learning disabilities speak up /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/7788.
Krigström, Rasmus. "Learning Tracks : En studie om auditiva hjälpmedel vid instudering av körmusik." Thesis, Kungl. Musikhögskolan, Institutionen för musik, pedagogik och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kmh:diva-4231.
Denna studie är gjord på ämnet learning tracks, dvs auditiva instuderingsfiler för vokalmusik. Det finns ingen historisk forskning eller annan tidigare forskning på ämnet men man vet att det har förekommit som fenomen inom genren barbershop lika länge som den portabla kassettbandspelaren, och på senare år utvecklats mycket i och med internet samt möjligheten att spela in och editera musik på en hemdator. Angränsande forskning om spegelneuroner, inlärning på gehör och körmetodik har studerats som forskningsgrund och det sociokulturella perspektivet samt variationsteori är studiens teoretiska perspektiv. Syftet med studien är att undersöka vilka variationer i musikaliskt resultat samt i elevernas upplevelse av instudering som kan urskiljas kopplat till notbaserad instudering av körmusik, respektive instudering med hjälp av instuderingsfiler som komplement. Två testgrupper, en som fick jobba med instuderingsfiler som komplement till noter och en som bara fick instudera med noter, jobbademed ett stycke musik under fyra lektionspass som observerades och ljud spelades in för att kunna följa progressionen i instuderingen. En enkät till samtliga elever som deltog som frågade om deras upplevelse av instuderingen fylldes i direkt efter studiens avslut. Resultatet var tydligt, både utifrån testgruppernas musikaliska prestation och ifrån deras egen upplevelse av instuderingen, instuderingsfiler var för dem bättre än enbart noter. Resultatet går även att tydligt knyta an till den angränsande tidigare forskningen på ämnet. Även om studien är tydlig behövs det mer forskning inom detta område. This study is on the subject of music learning tracks for learning a capella music. While there is no specific research on the subject yet it has been known as a phenomenon in the genre of barbershop harmony for as long as the tape recorder has been around, and has grown into a well-established business because of the internet and the possibilities of editing music on home computers. Earlier research in surrounding areas such as choir methodology, ear training and mirror neurons have laid the research ground for the study, and the theoretical perspectives which the data was analyzed through are the sociocultural perspective and variation theory. The purpose of this study is to explore variations in musical results and the pupils experience of learning that can be detected between a group that studies with learning tracks and a group that studies without learning tracks. The two groups were followed learning the same piece of music during four classes through observation and recording of sound. Directly following the last class, the students answered a survey about their experience of the learning process. The results were clear, both from the difference in musical results and from the answers in the survey, learning tracks are better for learning new music than just using sheet music. The results also connect to earlier research in surrounding areas, but even though the results of this study are clear more research is needed in this specific area.
5
Brodin, Johan. "Working with emotions : Recommending subjective labels to music tracks using machine learning." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199278.
Curated music collection is a growing field as a result of the freedom and supply that streaming music services like Spotify provide us with. To be able to categorize music tracks based on subjective core values in a scalable manner, this thesis has explored if recommending such labels are possible through machine learning. When analysing 2464 tracks with one or more of the 22 different core values a profile was built up for each track by features from three different categories: editorial, cultural and acoustic. When classifying the tracks into core values different methods of multi-label classification were explored. By combining five different transformation approaches with three base classifiers and using two algorithm adaptations a total of 17 different configurations were constructed. The different configu- rations were evaluated with multiple measurements including (but not limited to) Hamming Loss, Ranking Loss, One error, F1 score, exact match and both training and testing time. The results showed that the problem transformation algorithm Label Powerset together with Sequential minimal optimization outper- formed the other configurations. We also found promising results for neural networks, something that should be investigated further in the future. Kurerade musiksamlingar är ett växande område som en direkt följd av den frihet som strömmande musiktjänster som Spotify ger oss. För att kunna kategorisera låtar baserade på subjektiva värderingar på ett skalbart sätt har denna avhandling undersökt om rekommendationer av sådana etiketter är möjliga genom maskininlärning. När 2464 spår med ett eller flera av 22 olika kärnvärden analyserades byggdes en profil för varje spår upp av attribut från tre olika kategorier: redaktionella, kulturella och akustiska. Vid klassificering av spåren undersöktes flera olika metoder för fleretikettsklassificering. Genom att kombinera fem olika transformationsmetoder med tre bas-klassificerare och använda två algoritm-anpassningar konstruerades totalt 17 olika konfigurationer. De olika konfigurationerna utvärderades med flera olika mätvärden, inkluderat (men inte begränsat till) Hamming Loss, Ranking Loss, One error, F1 score, exakt matchning och både träningstid och testningstid. Resultaten visade att transformationsalgoritmen ”Label Powerset” tillsammans med Sekventiell Minimal Optimering utklassade de andra konfigurationerna. Vi fann också lovande resultat för artificiella neuronnät, något som bör undersökas ytterligare i framtiden.
6
Howell, Jamie Robert. "Learning through stories : An investigation into how Tracks Rites of Passage Programme impacts on the development of young men and their family systems." Thesis, University of Canterbury. Educational Studies and Leadership, 2012. http://hdl.handle.net/10092/7611.
The Tracks rites of passage are processes that mark the adolescent transition, for the participant, the family and the community, between the two life stages of childhood and adulthood. Adolescent initiation rites offer a community led journey of separation, transition and integration as a way to work meaningfully with adolescents as they move between the life stages of childhood into adulthood. In Aotearoa/New Zealand the Tracks programme provides a five day contemporary rite of passage for adolescents and, where possible, their fathers. The rite of passage is based on the assumption that adolescents need opportunities to find their voices and make meaning if they are to become more aware of who they are and where they belong.
The methodology recognises that I, as researcher and insider in the Tracks organisation, needed to develop a holistic approach to insider research so that I could call on my understandings of the organisation and also guard against bias. The holistic approach involves the four interpenetrating strategies of appreciative inquiry, narrative inquiry, a blend of approaches to self-study that include meditation and critical reflection, and most importantly organic inquiry. The four strategies are based on coherence theories that describe learning as being organic, interconnected and emergent. Data were gathered from interviews and cycles of critical self-reflection in the form of a learning journal.
Data comes from interviews with the mother or fathers and young men of six families who have participated in the Tracks rite of passage programme. I have also discussed this work with a number of professionals in the field of youth work. The project found that Tracks had created conditions that empowered these young men with an increased capacity to make sense of their lives. Fathers expressed how challenging and rewarding they had found it to speak in honest terms with their sons, and that they were supported to do the inner work necessary to be able to speak in such ways. All of the family members expressed a need to have more support after the event.
The findings suggest a need to explore further the nature of the work happening at Tracks. It validates Lashlie’s (2005) theory that adolescents need their fathers and other men to be involved in their lives at the time of transition. Tracks also helps fathers to get to grips with the inner work of developing emotional maturity. The work happening at Tracks invites further research into and debate on the value of emotional intelligence. The Tracks rite of passage offers an alternative perspective to understand the unacceptably high rates of adolescent morbidity and mortality happening in New Zealand.
7
Li, Jingxian. "Reinforcement learning using sensorimotor traces." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45590.
The skilled motions of humans and animals are the result of learning good solutions
to difficult sensorimotor control problems. This thesis explores new models
for using reinforcement learning to acquire motion skills, with potential applications
to computer animation and robotics. Reinforcement learning offers a principled
methodology for tackling control problems. However, it is difficult to apply
in high-dimensional settings, such as the ones that we wish to explore, where the
body can have many degrees of freedom, the environment can have significant
complexity, and there can be further redundancies that exist in the sensory representations
that are available to perceive the state of the body and the environment.
In this context, challenges to overcome include: a state space that cannot be fully
explored; the need to model how the state of the body and the perceived state of
the environment evolve together over time; and solutions that can work with only
a small number of sensorimotor experiences.
Our contribution is a reinforcement learning method that implicitly represents
the current state of the body and the environment using sensorimotor traces. A
distance metric is defined between the ongoing sensorimotor trace and previously
experienced sensorimotor traces and this is used to model the current state as a
weighted mixture of past experiences. Sensorimotor traces play multiple roles in
our method: they provide an embodied representation of the state (and therefore
also the value function and the optimal actions), and they provide an embodied
model of the system dynamics.
In our implementation, we focus specifically on learning steering behaviors for
a vehicle driving along straight roads, winding roads, and through intersections.
The vehicle is equipped with a set of distance sensors. We apply value-iteration using off-policy experiences in order to produce control policies capable of steering
the vehicle in a wide range of circumstances. An experimental analysis is provided
of the effect of various design choices.
In the future we expect that similar ideas can be applied to other high-dimensional
systems, such as bipedal systems that are capable of walking over variable terrain,
also driven by control policies based on sensorimotor traces.
8
Taylor, Teresa Brooks. "Service-Learning/Civic Engagement Track." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/3632.
Cette thèse porte sur la conception d’outils interactifs pour comprendre et faciliter l’apprentissage de la danse à partir de vidéos. Les processus d’apprentissage des danseurs représentent une source d’informations riches pour les chercheurs qui s’intéressent à la conception de systèmes soutenant l’apprentissage moteur. En effet, les danseurs experts réutilisent un large éventail de compétences qu’ils ont appris. Cependant, ces compétences sont en partie le résultat de connaissances implicites et incarnées,qui sont difficilement exprimables et verbalisables par un individu.Dans cette thèse, je soutiens que nous pouvons capturer et sauvegarder une trace des connaissances implicites des danseurs et les utiliser pour concevoir des outils interactifs qui soutiennent l’apprentissage de la danse. Mon approche consiste à étudier différentes sessions d’apprentissage de danse dans des contextes réels, aussi bien individuels que collaboratifs.Sur la base des résultats apportés par ces études, je contribue à une meilleure compréhension des processus implicites qui sous-tendent l’apprentissage de la danse dans des contextes individuels et collectifs. Je présente plusieurs stratégies d’apprentissage utilisées par des danseurs et j’affirme que l’on peut documenter ces stratégies en sauvegardant une trace de l’apprentissage. Je discute de l’opportunité que représente la capture de ces connaissances incarnées et j’apporte de nouvelles perspectives pour la conception d’outils d’aide à l’apprentissage du mouvement par la vidéo This thesis focuses on designing interactive tools to understand and support dance learning from videos. Dancers' learning practice represents a rich source of information for researchers interested in designing systems that support motor learning. Indeed, dancers embody a wide range of skills that they reuse during new dance sequences learning. However, these skills are in part the result of embodied implicit knowledge. In this thesis, I argue that we can capture and save traces of dancers' embodied knowledge and use them to design interactive tools that support dance learning. My approach is to study real-life dance learning tasks in individual and collaborative settings. Based on the findings from all the studies, I discuss the challenge of capturing embodied knowledge to support dancers’ learning practice. My thesis highlights that although dancers’ learning processes are diverse, similar strategies emerge to structure their learning process. Finally, I bring and discuss new perspectives to the design of movement-based learning tools
10
Meza, Fernandez Sandra. "Enseigner et apprendre en ligne : vers un modèle de la navigation sur des sites Web de formation universitaire." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-00974481.
Cette thèse propose de cartographier le parcours de navigation des usagers des EIAH pour le visualiser, visualiser pour interpréter et interpréter pour anticiper. Les profils d'apprentissage ont une influence sur les modes de navigation dans un environnement d'apprentissage en ligne. S'appuyant sur une méthodologie capable de modéliser le parcours de navigation d'un usager et d'anticiper son prochain clic sur une plateforme, notre étude cherche à élargir le champ des connaissances de l'efficacité/performance des styles d'apprentissage. La méthodologie utilisée repose sur l'analyse des traces d'utilisation élaborée à partir de 63 archives logs Web, incluant 4637 lignes de registre et 13 206 possibilités de choix de module. Le travail de recherche s'inscrit dans le cadre d'approches associant sémiologie, des sciences de l'information, psychologie cognitive et sciences de l'éducation. Trois observations ont été menées, générant des informations sur le profil de l'usager, la représentation des parcours et l'impact du style d'apprentissage dans le choix des fonctionnalités de travail offertes disponibles sur la plateforme. Les principaux résultats sont de deux types : d'une part, l'élaboration d'un outil convertissant les traces des fichiers log en parcours de navigation, et d'autre part, la confirmation d'un lien entre style d'apprentissage et mode de navigation. Ce deuxième résultat permet d'élaborer une méthode d'anticipation du nouveau choix de module sur une plateforme numérique de travail. Les applications pratiques visant à rendre exploitables ces traces dans les formations universitaires sont l'élaboration de bilans de qualité (ressources préférées, fonctionnalités moins utilisées) et l'identification des besoins de médiation pédagogique pour la compréhension de la tâche ou du processus (identifié par exemple dans l'insistance sur le module de consignes, le temps investi par un groupe ou par des trajets répétés). Cette thèse s'adresse principalement aux responsables pédagogiques universitaires décideurs de l'intégration des TIC, et par extension, aux étudiants universitaires et aux concepteurs d'outils d'apprentissage.
Lawlor, Michael. Inner track learning: Exercises in vizualization, relaxation and energy raising to accompany the book "Inner track learning" by Michael Lawlor. [Kemble]: [Centre for Inner Development in Business], 1988.
Oliver, Nuria, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, and Jose A. Lozano, eds. Machine Learning and Knowledge Discovery in Databases. Research Track. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86486-6.
Oliver, Nuria, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, and Jose A. Lozano, eds. Machine Learning and Knowledge Discovery in Databases. Research Track. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86520-7.
Oliver, Nuria, Fernando Pérez-Cruz, Stefan Kramer, Jesse Read, and Jose A. Lozano, eds. Machine Learning and Knowledge Discovery in Databases. Research Track. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86523-8.
Jin, Yue, Dimitre Kostadinov, Makram Bouzid, and Armen Aghasaryan. "Common Structures in Resource Management as Driver for Reinforcement Learning: A Survey and Research Tracks." In Machine Learning for Networking, 117–32. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19945-6_8.
Zhang, Jun, and Jian Jin. "Regularized Extreme Learning Machine Ensemble Using Bagging for Tropical Cyclone Tracks Prediction." In Lecture Notes in Computer Science, 203–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02698-1_18.
Krishna Chythanya, N., K. Madhavi, and G. Ramesh. "A Machine Learning Enabled IoT Device to Combat Elephant Mortality on Railway Tracks." In Innovative Data Communication Technologies and Application, 531–41. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9651-3_44.
Bergmeir, Christoph, Gregorio Sáinz, Carlos Martínez Bertrand, and José Manuel Benítez. "A Study on the Use of Machine Learning Methods for Incidence Prediction in High-Speed Train Tracks." In Recent Trends in Applied Artificial Intelligence, 674–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38577-3_70.
Tresilian, James. "Staying on Track." In Sensorimotor Control and Learning, 521–70. London: Macmillan Education UK, 2012. http://dx.doi.org/10.1007/978-1-137-00511-3_10.
Lax, Sara. "Discovering Traces of the Past …" In Out There Learning, edited by Deborah Louise Curran, Cameron Owens, Helga Thorson, and Elizabeth Vibert, 107–8. Toronto: University of Toronto Press, 2019. http://dx.doi.org/10.3138/9781487519469-013.
Morrell, Amish. "Traces and Transformation." In Expanding the Boundaries of Transformative Learning, 229–39. New York: Palgrave Macmillan US, 2002. http://dx.doi.org/10.1007/978-1-349-63550-4_18.
Ferreira, João Filipe, and Jorge Dias. "Probabilistic Learning." In Springer Tracts in Advanced Robotics, 147–67. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02006-8_6.
Shimoda, Shingo. "Tacit Learning – Machine Learning Paradigm Based on the Principles of Biological Learning." In Springer Tracts in Advanced Robotics, 213–34. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12922-8_8.
Тези доповідей конференцій з теми "Learning tracks":
1
Karampiperis, Pythagoras, and Demetrios Sampson. "Designing learning services." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062893.
Verbert, Katrien, Dragan Gašević, Jelena Jovanović, and Erik Duval. "Ontology-based learning content repurposing." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062908.
Pretet, Laure, Gael Richard, and Geoffroy Peeters. "Learning to Rank Music Tracks Using Triplet Loss." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053135.
Xu, Jun, Yunbo Cao, Hang Li, and Min Zhao. "Ranking definitions with supervised learning methods." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062761.
Punera, Kunal, Suju Rajan, and Joydeep Ghosh. "Automatically learning document taxonomies for hierarchical classification." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062843.
Kashihara, Akihiro, and Shinobu Hasegawa. "Learning how to learn with web contents." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062880.
S, Pradeep, Chitra Ramachandran, and Srinath Srinivasa. "Towards autonomic web-sites based on learning automata." In Special interest tracks and posters of the 14th international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1062745.1062860.
Ben Sassi, Manel, and Mona Laroussi. "The engineering of tracks for the standard IMS LD: Learners tracks' analysis for tailorable educational scenario based on IMS LD standard." In 2012 International Conference on Education and e-Learning Innovations (ICEELI 2012). IEEE, 2012. http://dx.doi.org/10.1109/iceeli.2012.6360652.
Bousbia, Nabila, Amar Balla, and Issam Rebai. "Measuring the learners' learning style based on tracks analysis in web based learning." In 2009 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2009. http://dx.doi.org/10.1109/iscc.2009.5202282.
Human beings are constantly improving their cognitive ability via automatic learning from the interaction with the environment. Two important aspects of automatic learning are the visual perception and knowledge acquisition. The fusion of these two aspects is vital for improving the intelligence and interaction performance of robots. Many automatic knowledge extraction and recognition methods have been widely studied. However, little work focuses on integrating automatic knowledge extraction and recognition into a unified framework to enable jointly visual perception and knowledge acquisition. To solve this problem, we propose a Dual Track Multimodal Automatic Learning (DTMAL) system, which consists of two components: Hybrid Incremental Learning (HIL) from the vision track and Multimodal Knowledge Extraction (MKE) from the knowledge track. HIL can incrementally improve recognition ability of the system by learning new object samples and new object concepts. MKE is capable of constructing and updating the multimodal knowledge items based on the recognized new objects from HIL and other knowledge by exploring the multimodal signals. The fusion of the two tracks is a mutual promotion process and jointly devote to the dual track learning. We have conducted the experiments through human-machine interaction and the experimental results validated the effectiveness of our proposed system.
Звіти організацій з теми "Learning tracks":
1
Ilghami, Okhtay, Dana S. Nau, Hector Munoz-Avila, and David W. Aha. Learning Preconditions for Planning from Plan Traces and HTN Structure. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada448060.
Pape, Barbara, and Tom Vander Ark. Policies and Practices That Meet Learners Where They Are. Digital Promise, 2018. http://dx.doi.org/10.51388/20.500.12265/15.
The convergence of growing classroom diversity, learning sciences research, sophistication of technology, and 21st- century job requirements in a global market could put America’s education system on track for personalizing the learning experience. The goal is for each student to master content and skills to help guarantee their success in college and career. We need to re-think our education system to address learner variability and meet our promise to guide each learner to become productive and ful lled citizens.
3
Dubeck, Margaret M., Jonathan M. B. Stern, and Rehemah Nabacwa. Learning to Read in a Local Language in Uganda: Creating Learner Profiles to Track Progress and Guide Instruction Using Early Grade Reading Assessment Results. RTI Press, June 2021. http://dx.doi.org/10.3768/rtipress.2021.op.0068.2106.
The Early Grade Reading Assessment (EGRA) is used to evaluate studies and monitor projects that address reading skills in low- and middle-income countries. Results are often described solely in terms of a passage-reading subtask, thereby overlooking progress in related skills. Using archival data of cohort samples from Uganda at two time points in three languages (Ganda, Lango, and Runyankore-Rukiga), we explored a methodology that uses passage-reading results to create five learner profiles: Nonreader, Beginner, Instructional, Fluent, and Next-Level Ready. We compared learner profiles with results on other subtasks to identify the skills students would need to develop to progress from one profile to another. We then used regression models to determine whether students’ learner profiles were related to their results on the various subtasks. We found membership in four categories. We also found a shift in the distribution of learner profiles from Grade 1 to Grade 4, which is useful for establishing program effectiveness. The distribution of profiles within grades expanded as students progressed through the early elementary grades. We recommend that those who are discussing EGRA results describe students by profiles and by the numbers that shift from one profile to another over time. Doing so would help describe abilities and instructional needs and would show changes in a meaningful way.
4
Field, Adrian. Menzies School Leadership Incubator: Insights. Australian Council for Educational Research, July 2021. http://dx.doi.org/10.37517/978-1-74286-637-6.
The Menzies School Leadership Incubator (the Incubator) is a national trans-disciplinary initiative to design, test and learn about transformative innovations that will support lasting systems change in Australian schools’ leadership. This review explores the successes, challenges and learning from work in the Incubator to date, from the perspective of a collaborative seeking longstanding systems change. The design of the review is informed by thinking in the innovation literature, principally communities of practice and socio-technical systems theory. This review was undertaken as a rapid exploration of experiences and learning, drawing on interviews with eight individuals from within the Incubator (six interviews) and collaborating partners (two interviews).
5
Millington, Kerry, and Samantha Reddin. COVID-19 Health Evidence Summary No.109. Institute of Development Studies (IDS), January 2021. http://dx.doi.org/10.19088/k4d.2021.012.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Epidemiology and modelling; Therapeutics; Vaccines; Social Science; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events.
6
Millington, Kerry. COVID-19 Health Evidence Summary No.113. Institute of Development Studies (IDS), February 2021. http://dx.doi.org/10.19088/k4d.2021.023.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Infection Prevention and Control; Therapeutics; Vaccines; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs and Online learning & events.
7
Millington, Kerry, and Samantha Reddin. COVID-19 Health Evidence Summary No.108. Institute of Development Studies (IDS), January 2021. http://dx.doi.org/10.19088/k4d.2021.007.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Testing; Therapeutics; Vaccines; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events
8
Millington, Kerry. COVID-19 Health Evidence Summary No.115. Institute of Development Studies (IDS), March 2021. http://dx.doi.org/10.19088/k4d.2021.030.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Infection Prevention and Control; Therapeutics; Vaccines; Indirect impact of COVID-19; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events.
9
Millington, Kerry. COVID-19 Health Evidence Summary No.116. Institute of Development Studies (IDS), March 2021. http://dx.doi.org/10.19088/k4d.2021.035.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Epidemiology and modelling; Therapeutics; Vaccines; Indirect impact of COVID-19; Health systems; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs and Online learning & events.
10
Piotrowski, Helen. COVID-19 Health Evidence Summary No.121. Institute of Development Studies (IDS), April 2021. http://dx.doi.org/10.19088/k4d.2021.065.
This weekly COVID-19 health evidence summary (HES) is based on 3.5 hours of desk-based research. The summary is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they should go to before making decisions. This summary covers publications on Clinical characteristics and management; Therapeutics; Vaccines; Leadership and governance; Health systems; Comments, Editorials, Opinions, Blogs, News; Dashboards & Trackers; C19 Resource Hubs; and Online learning & events.
