Готові списки джерел за темами / Action algorithms

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Добірка наукової літератури з теми "Action algorithms"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 липня 2025

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Статті в журналах з теми "Action algorithms"

Moraes, Rubens O., Mario A. Nascimento, and Levi H. S. Lelis. "Asymmetric Action Abstractions for Planning in Real-Time Strategy Games." Journal of Artificial Intelligence Research 75 (November 30, 2022): 1103–37. http://dx.doi.org/10.1613/jair.1.13769.

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Action abstractions restrict the number of legal actions available for real-time planning in zero-sum extensive-form games, thus allowing algorithms to focus their search on a set of promising actions. Even though unabstracted game trees can lead to optimal policies, due to real-time constraints and the tree size, they are not a practical choice. In this context, we introduce an action abstraction scheme which we call asymmetric action abstraction. Asymmetric abstractions allow search algorithms to “pay more attention” to some aspects of the game by unevenly dividing the algorithm’s search eff

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Geißer, Florian, David Speck, and Thomas Keller. "Trial-Based Heuristic Tree Search for MDPs with Factored Action Spaces." Proceedings of the International Symposium on Combinatorial Search 11, no. 1 (2021): 38–47. http://dx.doi.org/10.1609/socs.v11i1.18533.

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MDPs with factored action spaces, i.e., where actions are described as assignments to a set of action variables, allow reasoning over action variables instead of action states, yet most algorithms only consider a grounded action representation. This includes algorithms that are instantiations of the Trial-based Heuristic Tree Search (THTS) framework, such as AO* or UCT. To be able to reason over factored action spaces, we propose a generalization of THTS where nodes that branch over all applicable actions are replaced with subtrees that consist of nodes that represent the decision for a single

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Gite, Shilpa, and Himanshu Agrawal. "Early Prediction of Driver's Action Using Deep Neural Networks." International Journal of Information Retrieval Research 9, no. 2 (2019): 11–27. http://dx.doi.org/10.4018/ijirr.2019040102.

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Intelligent transportation systems (ITSs) are one of the most widely-discussed and researched topic across the world. The researchers have focused on the early prediction of a driver's movements before drivers actually perform actions, which might suggest a driver to take a corrective action while driving and thus, avoid the risk of an accident. This article presents an improved deep-learning technique to predict a driver's action before he performs that action, a few seconds in advance. This is considering both the inside context (of the driver) and the outside context (of the road), and fuse

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Fathi, Yahya, and Craig Tovey. "Affirmative action algorithms." Mathematical Programming 34, no. 3 (1986): 292–301. http://dx.doi.org/10.1007/bf01582232.

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Wu, Songjiao. "Image Recognition of Standard Actions in Sports Videos Based on Feature Fusion." Traitement du Signal 38, no. 6 (2021): 1801–7. http://dx.doi.org/10.18280/ts.380624.

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Standard actions are crucial to sports training of athletes and daily exercise of ordinary people. There are two key issues in sports action recognition: the extraction of sports action features, and the classification of sports actions. The existing action recognition algorithms cannot work effectively on sports competitions, which feature high complexity, fine class granularity, and fast action speed. To solve the problem, this paper develops an image recognition method of standard actions in sports videos, which merges local and global features. Firstly, the authors combed through the funct

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Moraes, Rubens, Julian Mariño, Levi Lelis, and Mario Nascimento. "Action Abstractions for Combinatorial Multi-Armed Bandit Tree Search." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 14, no. 1 (2018): 74–80. http://dx.doi.org/10.1609/aiide.v14i1.13018.

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Search algorithms based on combinatorial multi-armed bandits (CMABs) are promising for dealing with state-space sequential decision problems. However, current CMAB-based algorithms do not scale to problem domains with very large actions spaces, such as real-time strategy games played in large maps. In this paper we introduce CMAB-based search algorithms that use action abstraction schemes to reduce the action space considered during search. One of the approaches we introduce use regular action abstractions (A1N), while the other two use asymmetric action abstractions (A2N and A3N). Empirical r

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Le, Hai S., Brendan Juba, and Roni Stern. "Learning Safe Action Models with Partial Observability." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 18 (2024): 20159–67. http://dx.doi.org/10.1609/aaai.v38i18.29995.

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A common approach for solving planning problems is to model them in a formal language such as the Planning Domain Definition Language (PDDL), and then use an appropriate PDDL planner. Several algorithms for learning PDDL models from observations have been proposed but plans created with these learned models may not be sound. We propose two algorithms for learning PDDL models that are guaranteed to be safe to use even when given observations that include partially observable states. We analyze these algorithms theoretically, characterizing the sample complexity each algorithm requires to guaran

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Hou, Yueqi, Xiaolong Liang, Jiaqiang Zhang, Qisong Yang, Aiwu Yang, and Ning Wang. "Exploring the Use of Invalid Action Masking in Reinforcement Learning: A Comparative Study of On-Policy and Off-Policy Algorithms in Real-Time Strategy Games." Applied Sciences 13, no. 14 (2023): 8283. http://dx.doi.org/10.3390/app13148283.

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Invalid action masking is a practical technique in deep reinforcement learning to prevent agents from taking invalid actions. Existing approaches rely on action masking during policy training and utilization. This study focuses on developing reinforcement learning algorithms that incorporate action masking during training but can be used without action masking during policy execution. The study begins by conducting a theoretical analysis to elucidate the distinction between naive policy gradient and invalid action policy gradient. Based on this analysis, we demonstrate that the naive policy gr

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Rani, Seema, and Saurabh Charaya. "Improving the Performance of OLSR in Wireless Networks using Reinforcement Learning Algorithms." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 166–72. http://dx.doi.org/10.17762/ijritcc.v11i7s.6988.

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The Optimized Link State Routing Protocol is a popular proactive routing protocol used in wireless mesh networks. However, like many routing protocols, OLSR can suffer from inefficiencies and suboptimal performance in certain network conditions. To address these issues, researchers have proposed using reinforcement learning algorithms to improve the routing decisions made by OLSR. This paper explores the use of three RL algorithms - Q-Learning, SARSA, and DQN - to improve the performance of OLSR. Each algorithm is described in detail, and their application to OLSR is explained. In particular,

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Yang, Jianhua. "A Deep Learning and Clustering Extraction Mechanism for Recognizing the Actions of Athletes in Sports." Computational Intelligence and Neuroscience 2022 (March 24, 2022): 1–9. http://dx.doi.org/10.1155/2022/2663834.

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In sports, the essence of a complete technical action is a complete information structure pattern and the athlete’s judgment of the action is actually the identification of the movement information structure pattern. Action recognition refers to the ability of the human brain to distinguish a perceived action from other actions and obtain predictive response information when it identifies and confirms it according to the constantly changing motion information on the field. Action recognition mainly includes two aspects: one is to obtain the required action information based on visual observati

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Дисертації з теми "Action algorithms"

Cox, Jürgen 1970. "Solution of sign and complex action problems with cluster algorithms." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8646.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2001. Includes bibliographical references (p. [105]-109) and index. Two kinds of models are considered which have a Boltzmann weight which is either not real or real but not positive and so standard Monte Carlo methods are not applicable. These sign or complex action problems are solved with the help of cluster algorithms. In each case improved estimators for the Boltzmann weight are constructed which are real and positive. The models considered belong to two classes: fermionic and non-fermionic models. An example

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Wanek, J. F. "Direct action of radiation on mummified cells : modelling of computed tomography by Monte Carlo algorithms." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1432807/.

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X-ray imaging is a non-destructive and preferred method in paleopathology to reconstruct the history of ancient diseases. Sophisticated imaging technologies such as computed tomography (CT) have become common for the investigation of skeletal disorders in human remains. The effects of CT exposure on ancient cells have not been quantitatively examined in the past and may be important for subsequent genetic analysis. To remedy this shortcoming, different Monte Carlo models were developed to simulate X-ray irradiation on ancient cells. Effects of mummification and physical processes were consider

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Oppon, Ekow CruickShank. "Synergistic use of promoter prediction algorithms: a choice of small training dataset?" Thesis, University of the Western Cape, 2000. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_8222_1185436339.

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Promoter detection, especially in prokaryotes, has always been an uphill task and may remain so, because of the many varieties of sigma factors employed by various organisms in transcription. The situation is made more complex by the fact, that any seemingly unimportant sequence segment may be turned into a promoter sequence by an activator or repressor (if the actual promoter sequence is made unavailable). Nevertheless, a computational approach to promoter detection has to be performed due to number of reasons. The obvious that comes to mind is the long and tedious process involved in eluc

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Umuhoza, Denise. "Metric of trust for mobile ad hoc networks using source routing algorithms." Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_8946_1183465240.

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This thesis proposed and presented technical details of new probabilistic metrics of trust in the links wireless ad hoc networks for unobservable communications. In covert communication networks, only the end nodes are aware of the communication characteristics of the overall path. The most widely used protocols of ad hoc networks was overviewed. The routing protocols of ad hoc networks with trust considerations and select Destination Sequence Routing, a protocol that can be used in distributed ad hoc network settings for path discovery, was also reviewed. It establishes a path through whic

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Munaro, Matteo. "Robust perception of humans for mobile robots RGB-depth algorithms for people tracking, re-identification and action recognition." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423652.

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Human perception is one of the most important skills for a mobile robot sharing its workspace with humans. This is not only true for navigation, because people have to be avoided differently than other obstacles, but also because mobile robots must be able to truly interact with humans. In a near future, we can imagine that robots will be more and more present in every house and will perform services useful to the well-being of humans. For this purpose, robust people tracking algorithms must be exploited and person re-identification techniques play an important role for allowing robots to

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MONTELEONE, Vito. "WATCHING PEOPLE: ALGORITHMS TO STUDY HUMAN MOTION AND ACTIVITIES." Doctoral thesis, Università degli Studi di Palermo, 2020. http://hdl.handle.net/10447/395224.

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Nowadays human motion analysis is one of the most active research topics in Computer Vision and it is receiving an increasing attention from both the industrial and scientific communities. The growing interest in human motion analysis is motivated by the increasing number of promising applications, ranging from surveillance, human–computer interaction, virtual reality to healthcare, sports, computer games and video conferencing, just to name a few. The aim of this thesis is to give an overview of the various tasks involved in visual motion analysis of the human body and to present the issues

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Brualla, Barberà Llorenç. "Path integral Monte Carlo. Algorithms and applications to quantum fluids." Doctoral thesis, Universitat Politècnica de Catalunya, 2002. http://hdl.handle.net/10803/6577.

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Path integral Monte Carlo (PIMC) is a method suitable for quantum liquid simulations at finite temperature. We present in this thesis a study of PIMC dealing with the theory and algorithms related to it, and then two applications of PIMC to current research problems of quantum fluids in the Bolzmann regime. The first part encompasses a study of the different ingredients of a PIMC code: action, sampling and physical property estimators. Particular attention has been paid to Li-Broughton's higher order approximation to the action. Regarding sampling, several collective movement methods have

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Празднікова, Маргарита Олександрівна. "Додаток на базі Android «Кіногід» для керування контентом". Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/34968.

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Структура та обсяг роботи. Пояснювальна записка дипломного проекту складається з шести розділів, містить 8 рисунків, 5 таблиць, 5 додатка, 45 джерел. Дипломний проект присвячений розробці додатку на базі Android “Кіногід”. У розділі аналіз існуючих рішень для систематизації інформації про кінопокази розглянуть існуючі сервіси їх функції та недоліки, які необхідно вдосконалити. У розділі аналіз мов програмування та технології розроблення Android додатку розглянуті теоретичні аспекти методів виконання завданяя всі можливі ускладнення та недоліки різних систем у розробці Android додатку. Т

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Stephanos, Dembe. "Machine Learning Approaches to Dribble Hand-off Action Classification with SportVU NBA Player Coordinate Data." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/etd/3908.

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Recently, strategies of National Basketball Association teams have evolved with the skillsets of players and the emergence of advanced analytics. One of the most effective actions in dynamic offensive strategies in basketball is the dribble hand-off (DHO). This thesis proposes an architecture for a classification pipeline for detecting DHOs in an accurate and automated manner. This pipeline consists of a combination of player tracking data and event labels, a rule set to identify candidate actions, manually reviewing game recordings to label the candidates, and embedding player trajectories in

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Gill, Harnavpreet Singh. "Computationally Robust Algorithms for Hypoid Gear Cutting and Contact Line Determination using Ease-Off Methodology." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587499768039312.

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Книги з теми "Action algorithms"

Killingbeck, J. P. Microcomputer algorithms: Action from algebra. Adam Hilger, 1991.

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Pintér, J. Global optimization in action: Continuous and Lipschitz optimization--algorithms, implementations, and applications. Kluwer Academic Publishers, 1996.

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Doellgast, Virginia, Shruti Appalla, Dina Ginzburg, Jeonghun Kim, and Wen Li Thian. Global case studies of social dialogue on AI and algorithmic management. ILO, 2025. https://doi.org/10.54394/voqe4924.

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Employers are adopting and refining artificial intelligence (AI) and algorithm-based tools in the workplace, with wide-ranging implications for work and employment. This working paper examines case studies of social dialogue on AI at national, regional, sectoral, company, and workplace levels in Europe, North America, Asia, South America and the Caribbean, and Africa. Findings are organized around three distinct ‘action fields’ in which worker representatives have sought to influence strategies and outcomes associated with the growing use of AI and algorithms in the workplace. These include th

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Quadflieg, Sven, Klaus Neuburg, and Simon Nestler, eds. (Dis)Obedience in Digital Societies. transcript Verlag, 2022. http://dx.doi.org/10.14361/9783839457634.

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Algorithms are not to be regarded as a technical structure but as a social phenomenon - they embed themselves, currently still very subtle, into our political and social system. Algorithms shape human behavior on various levels: they influence not only the aesthetic reception of the world but also the well-being and social interaction of their users. They act and intervene in a political and social context. As algorithms influence individual behavior in these social and political situations, their power should be the subject of critical discourse - or even lead to active disobedience and to th

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Munerman, Viktor, Vadim Borisov, and Aleksandra Kononova. Mass data processing. Algebraic models and methods. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1906037.

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The monograph is devoted to mathematical and algorithmic support of mass data processing based on algebraic models. One of the most common classes of mass processing is considered - processing of highly active structured data. The construction of algebraic models of data and calculations and methods of proving their correspondence are analyzed. Three algebraic systems are studied, which can be used both as data models and as models of calculations. The algebraic and axiomatic methods of proving the correspondence of these models are investigated. A proof of their correspondence is given: homom

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Biryulin, Vladimir, Aleksey None, Dar'ya Kudelina, Oleg Larin, and Anton Tancyura. Relay protection and automation systems elektroenergeticheskim. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1058880.

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The manual includes basic information about the element base of relay protection and automation, principles of operation and circuit implementation of various types of relay protection and automation systems, algorithms of calculation of parameters of the action of relay protection and automation. Designed for students in specialty "power and electrical engineering", as well as professionals involved in the design and operation of relay protection and automation of electric power systems.

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Kuo, Sen M. Active noise control systems: Algorithms and DSP implementations. Wiley, 1996.

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Juang, Jer-Nan. Deadbeat predictive controllers. National Aeronautics and Space Administration, Langley Research Center, 1997.

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Juang, Jer-Nan. Recursive deadbeat controller design. National Aeronautics and Space Administration, Langley Research Center, 1997.

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L, Palumbo Daniel, and Langley Research Center, eds. Performance of optimized actuator and sensor arrays in an active noise control system. National Aeronautics and Space Administration, Langley Research Center, 1996.

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Частини книг з теми "Action algorithms"

Bergel, Alexandre. "Genetic Algorithms in Action." In Agile Artificial Intelligence in Pharo. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5384-7_9.

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Fraczak, Wojciech. "Multi-action process algebra." In Algorithms, Concurrency and Knowledge. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60688-2_40.

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Gochet, Paul, Pascal Gribomont, and Didier Rossetto. "Algorithms for Relevant Logic." In Logic, Thought and Action. Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-3167-x_21.

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Garcez, Artur S. d’Avila, and Luis C. Lamb. "Cognitive Algorithms and Systems: Reasoning and Knowledge Representation." In Perception-Action Cycle. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1452-1_18.

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Kera, Denisa Reshef. "Public and Open Futures between Labor, Action, and Leisure." In Algorithms and Automation. Routledge India, 2023. http://dx.doi.org/10.4324/9781003189411-13.

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Mathew, Amal, and Akanksha. "Volleyball Action Recognition Based on Skeleton Data Using LSTM." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8868-2_31.

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Mirjalili, Seyedali, and Andrew Lewis. "Benchmark Function Generators for Single-Objective Robust Optimisation Algorithms." In Decision Science in Action. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0860-4_2.

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Haque, Shazia, Lars Kulik, and Alexander Klippel. "Algorithms for Reliable Navigation and Wayfinding." In Spatial Cognition V Reasoning, Action, Interaction. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75666-8_18.

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Zhang, Qi. "Cognitive Algorithms and Systems of Episodic Memory, Semantic Memory, and Their Learnings." In Perception-Action Cycle. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1452-1_13.

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Lima, Pedro U. "Cognitive Algorithms and Systems of Error Monitoring, Conflict Resolution and Decision Making." In Perception-Action Cycle. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1452-1_15.

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Тези доповідей конференцій з теми "Action algorithms"

Bian, Gui-Bin, Yaqin Peng, Li Zhang, Jun Li, and Zhen Li. "Algorithms in Surgical Action Recognition: A Survey." In 2024 IEEE International Conference on Real-time Computing and Robotics (RCAR). IEEE, 2024. http://dx.doi.org/10.1109/rcar61438.2024.10670748.

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Fu, Jiamin, Zhihong Chen, Haiwei Zhang, and Yuxuan Gao. "Optimizing action segmentation with linear self-attention and pyramidal pooling." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051722.

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Huang, Shuai. "Sports Action Recognition and Standardized Training using Puma Optimization Based Residual Network." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721909.

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Cutler, Jack, Baihua Li, Bashar Alhnaity, Tom Partridge, Mike Thompson, and Qinggang Meng. "AI for Sustainable Land Management and Greenhouse Gas Emission Forecasting: Advancing Climate Action." In 2025 4th Asia Conference on Algorithms, Computing and Machine Learning (CACML). IEEE, 2025. https://doi.org/10.1109/cacml64929.2025.11010973.

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Xu, Tao, and Zhangjin Huang. "SaccadeAction: A Fast and Accurate Action Tubelet Detector Based on Center and Corner Keypoints." In 2025 8th International Conference on Advanced Algorithms and Control Engineering (ICAACE). IEEE, 2025. https://doi.org/10.1109/icaace65325.2025.11019860.

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Zhao, Bei. "Evaluating Quality of College English Classroom Teaching based on Action Recognition using Genetic Algorithm based Multilayer Perceptron." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721822.

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Sabarish, R., R. Hariharan, R. J. Golden Renjith Nimal, and R. Sangamaeswaran. "Automotive Multi-Leaf Spring Design and Optimization through FEA." In International Conference on Design, Materials and Metaheuristic Algorithms for Engineering. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-4qyh6t.

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As a result of the high strength-to-weight ratio, the automobile industry is becoming increasingly interested in replacing steel springs with composite leaf springs. The task at hand is to swap out some steel springs for alloy springs. The car's suspension impacts how comfortable it is to drive and how much damage it sustains. The leaf spring group's primary role is to support the suspension element's vertical load. The contact between the blades makes adjusting the crossbow's action more difficult. The goal of this article is to replace steel multi-disc springs with single joint springs that

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Wang, Hanmo, Xiaojun Chang, Lei Shi, Yi Yang, and Yi-Dong Shen. "Uncertainty Sampling for Action Recognition via Maximizing Expected Average Precision." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/134.

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Recognizing human actions in video clips has been an important topic in computer vision. Sufficient labeled data is one of the prerequisites for the good performance of action recognition algorithms. However, while abundant videos can be collected from the Internet, categorizing each video clip is tedious and even time-consuming. Active learning is one way to alleviate the labeling labor by allowing the classifier to choose the most informative unlabeled instances for manual annotation. Among various active learning algorithms, uncertainty sampling is arguably the most widely-used strategy. Co

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Berkhout, Matthijs, and Koen Smit. "Utilizing Algorithms for Decision Mining Discovery." In Digital Restructuring and Human (Re)action. University of Maribor Press, 2022. http://dx.doi.org/10.18690/um.fov.4.2022.21.

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Organizations are executing operational decisions in fast changing environments, which increases the necessity for managing these decisions adequately. Information systems store information about such decisions in decision- and event logs that could be used for analyzing decisions. This study aims to find relevant algorithms that could be used to mine decisions from such decision- and event logs, which is called decision mining. By conducting a literature review, together with interviews conducted with experts with a scientific background as well as participants with a commercial background, r

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Patel, Apoorva D. "Wave Algorithms: Optimal Database Search and Catalysis." In QUANTUM COMPUTING: Back Action 2006. AIP, 2006. http://dx.doi.org/10.1063/1.2400898.

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Звіти організацій з теми "Action algorithms"

Rinuado, Christina, William Leonard, Christopher Morey, Theresa Coumbe, Jaylen Hopson, and Robert Hilborn. Artificial intelligence (AI)–enabled wargaming agent training. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48419.

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Fiscal Year 2021 (FY21) work from the Engineer Research and Development Center Institute for Systems Engineering Research lever-aged deep reinforcement learning to develop intelligent systems (red team agents) capable of exhibiting credible behavior within a military course of action wargaming maritime framework infrastructure. Building from the FY21 research, this research effort sought to explore options to improve upon the wargaming framework infrastructure and to investigate opportunities to improve artificial intelligence (AI) agent behavior. Wargaming framework infrastructure enhancement

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Synchak, Bohdan. Freedom of choice and freedom of action in the Ukrainian media. Ivan Franko National University of Lviv, 2022. http://dx.doi.org/10.30970/vjo.2022.51.11400.

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The article talks about the philosophical foundations that characterize the mechanism of internal inducement to action. As an academic, constitutional, and socio-ideological concept, the boundaries of freedom are outlined, which are displayed in the field of modern media space. The term «freedom» is considered as several philosophical concepts that formed the basis of the modern interpretation of this concept. The totality of its meanings is generalized into one that is adapted for the modern system. Parallels are drawn between the interaction of the concept of user freedom with the plane of d

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Li, Lingxi, Yaobin Chen, Renren Tian, Feng Li, Howell Li, and James R. Sturdevant. An Integrated Critical Information Delivery Platform for Smart Segment Dissemination to Road Users. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317440.

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An integrated critical information delivery platform for smart segment dissemination to road users was developed. A statewide baseline milepost geodatabase was created at 0.1-mile resolution with tools, protocols, and interfaces that allow other data sources to be efficiently utilized. A variety of data sources (e.g., INRIX, CARS, Doppler, camera images, connected vehicle data, automated vehicle location) were integrated into existing and new dashboards for stakeholders to monitor roadway conditions and after-action reviews. Additionally, based on these data sources, algorithms were developed

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Mintii, Iryna S., Svitlana V. Shokaliuk, Tetiana A. Vakaliuk, Mykhailo M. Mintii, and Vladimir N. Soloviev. Import test questions into Moodle LMS. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3271.

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The purpose of the study is to highlight the theoretical and methodological aspects of preparing the test questions of the most common types in the form of text files for further import into learning management system (LMS) Moodle. The subject of the research is the automated filling of the Moodle LMS test database. The objectives of the study: to analyze the import files of test questions, their advantages and disadvantages; to develop guidelines for the preparation of test questions of common types in the form of text files for further import into Moodle LMS. The action algorithms for import

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Ozkaya, Yusuf, Erdem Sariyuce, Umit Catalyurek, and Ali Pinar. Active Betweenness Cardinality: Algorithms and Applications. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1733256.

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de Luis, Mercedes, Emilio Rodríguez, and Diego Torres. Machine learning applied to active fixed-income portfolio management: a Lasso logit approach. Banco de España, 2023. http://dx.doi.org/10.53479/33560.

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The use of quantitative methods constitutes a standard component of the institutional investors’ portfolio management toolkit. In the last decade, several empirical studies have employed probabilistic or classification models to predict stock market excess returns, model bond ratings and default probabilities, as well as to forecast yield curves. To the authors’ knowledge, little research exists into their application to active fixed-income management. This paper contributes to filling this gap by comparing a machine learning algorithm, the Lasso logit regression, with a passive (buy-and-hold)

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Perdigão, Rui A. P. Information physics and quantum space technologies for natural hazard sensing, modelling and prediction. Meteoceanics, 2021. http://dx.doi.org/10.46337/210930.

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Disruptive socio-natural transformations and climatic change, where system invariants and symmetries break down, defy the traditional complexity paradigms such as machine learning and artificial intelligence. In order to overcome this, we introduced non-ergodic Information Physics, bringing physical meaning to inferential metrics, and a coevolving flexibility to the metrics of information transfer, resulting in new methods for causal discovery and attribution. With this in hand, we develop novel dynamic models and analysis algorithms natively built for quantum information technological platfor

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Moreland, Kenneth, Andrew Bauer, Berk Geveci, Patrick O'Leary, and Brad Whitlock. Leveraging production visualization tools in situ. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/44844.

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The visualization community has invested decades of research and development into producing large-scale production visualization tools. Although in situ is a paradigm shift for large-scale visualization, much of the same algorithms and operations apply regardless of whether the visualization is run post hoc or in situ. Thus, there is a great benefit to taking the large-scale code originally designed for post hoc use and leveraging it for use in situ. This chapter describes two in situ libraries, Libsim and Catalyst, that are based on mature visualization tools, VisIt and ParaView, respectively

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Bodson, Marc. Adaptive Algorithms for Active Noise and Vibration Control. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada390623.

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Borgwardt, Stefan, Walter Forkel, and Alisa Kovtunova. Finding New Diamonds: Temporal Minimal-World Query Answering over Sparse ABoxes. Technische Universität Dresden, 2019. http://dx.doi.org/10.25368/2023.223.

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Lightweight temporal ontology languages have become a very active field of research in recent years. Many real-world applications, like processing electronic health records (EHRs), inherently contain a temporal dimension, and require efficient reasoning algorithms. Moreover, since medical data is not recorded on a regular basis, reasoners must deal with sparse data with potentially large temporal gaps. In this paper, we introduce a temporal extension of the tractable language ELH⊥, which features a new class of convex diamond operators that can be used to bridge temporal gaps. We develop a com

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