Article
Education & Educational Research
Lok Cheung Shum, Yasmine Rosunally, Simon Scarle, Kamran Munir
Summary: When designing educational games, the traditional one size fits all approach of arranging the game context in a fixed sequence may not effectively support the diversity of players. This research proposes a personalised adaptation framework for designing educational serious games, which considers the player's ability and characteristics and adapts the game scenarios to their personal learning objectives and progress to achieve a non-linear learning sequence. The framework aims to provide students with personalised learning experiences and improve learning outcomes.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
Chanjuan Liu, Enqiang Zhu, Qiang Zhang, Xiaopeng Wei
Summary: This study introduces a new mathematical model of extensive games with limitations on computational resources for players' decision-making. It investigates the effects of computational costs on players' strategies and computational complexity, also conducting simulation experiments to explore the relationship between the amount of resources and the goodness of outcomes.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Andrew J. Collins, Sheida Etemadidavan
Summary: Although strategic coalition formation is traditionally modeled using cooperative game theory, actual human behavior often leads to different outcomes. This study compares the outcomes generated by human participants' behavior with those predicted by a cooperative game theory solution mechanism called the core partition. The experiment shows that core coalitions are found in about 42% of games, highlighting the complexity of finding core solutions.
Review
Biochemical Research Methods
Karthik Nagarajan, Congjian Ni, Ting Lu
Summary: This review provides a comprehensive overview of recent advances in agent-based modeling of microbial communities, including algorithms for simulating intracellular events, single-cell behaviors, intercellular interactions, and interactions between cells and their environments, as well as applications of agent-based modeling. It also discusses challenges and potential mitigation strategies.
ACS SYNTHETIC BIOLOGY
(2022)
Article
Acoustics
Zalan Borsos, Raphael Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matt Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, Neil Zeghidour
Summary: AudioLM is a framework for high-quality audio generation that maintains long-term consistency. It maps input audio to discrete tokens and treats audio generation as a language modeling task. This approach combines existing audio tokenizers to balance reconstruction quality and long-term structure, and leverages a hybrid tokenization scheme. By training on large corpora of raw audio waveforms, AudioLM learns to generate natural and coherent continuations. It can generate syntactically and semantically plausible speech continuations without any transcript or annotation, and even extend to generating coherent piano music continuations without symbolic representation.
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
(2023)
Article
Computer Science, Information Systems
Danial Hooshyar, Nour El Mawas, Marcelo Milrad, Yeongwook Yang
Summary: Data mining approaches have been successful in improving learners' interaction with educational computer games. However, there is a lack of research on the early prediction of learners' performance in educational games. In this research, a predictive modelling approach called GameEPM is proposed to estimate learners' final scores in an educational game for promoting computational thinking. The findings show that the GameEPM approach accurately and robustly estimates learners' performance at the early stages of the game.
Article
Computer Science, Information Systems
Eunice E. Santos, John Korah, Suresh Subramanian, Vairavan Murugappan, Elbert S. Huang, Neda Laiteerapong, Ali Cinar
Summary: Clinical practice guidelines play a critical role in standardizing practices in the medical community, but there is often a delay in adopting their recommendations. Various barriers such as clinical inertia and organizational culture hinder guideline dissemination, highlighting the need for a comprehensive computational model to improve dissemination strategies.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Neurosciences
Tamar Regev, Geffen Markusfeld, Leon Y. Deouell, Israel Nelken
Summary: The study revealed that the human auditory cortex is sensitive to the content of past stimulation and that neural responses measured at different latencies after stimulus onset are influenced by frequency intervals computed over distinct timescales. Early responses are more influenced by the history of stimulation than later responses. A model consisting of neural populations with frequency-specific but broad tuning can explain these results.
Article
Computer Science, Information Systems
Filippo Carnovalini, Antonio Roda, Paolo Caneva
Summary: Making music with others is a social activity that can enhance the well-being of individuals. Researchers have developed a serious game to enable non-musicians to interact and create rhythms collaboratively. The game analyzes real-time rhythms and provides synchronized musical feedback, enhancing the musical interaction and therapeutic effects.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Psychology, Multidisciplinary
Elaine Chew
Summary: This position paper proposes an innovative, multi-disciplinary approach to advancing knowledge on music performance, leveraging listeners' perception and experience to analyze music sequences. It also introduces the use of computational thinking to explore variations in expressions of cardiac arrhythmias.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Computer Science, Information Systems
Seungyeon Rhyu, Hyeonseok Choi, Sarah Kim, Kyogu Lee
Summary: Recent deep learning approaches have made remarkable progress in melody harmonization. This paper proposes a Transformer-based architecture that directly maps melody notes to chord sequences, generating structured chords with appropriate rhythms. Experimental results show that the proposed models generate chord sequences that are more structured and diverse than those generated by LSTM-based models.
Article
Computer Science, Artificial Intelligence
Weiming Bai, Zhipeng Zhang, Bing Li, Pei Wang, Yangxi Li, Congxuan Zhang, Weiming Hu
Summary: This study introduces a Large-Scale CG images Benchmark (LSCGB) and proposes a simple yet strong baseline model for forensic tasks. The benchmark has the advantages of large-scale, high diversity, and small bias. The baseline model improves forensic accuracy through a texture-aware network.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Computer Science, Information Systems
Ping Lou, Jiwei Hu, Cui Zhu, Junwei Yan, Liping Yuan
Summary: The emergence of service-oriented Cloud Manufacturing (CMfg) relies on technologies like cloud computing and Industrial Internet of Things to distribute and authorize various manufacturing resources. In CMfg, cooperation between multiple Manufacturing Services (MSs) is essential to complete Manufacturing Tasks (MTs) as individual and collective interests may conflict. By exploring individual decision-making behaviors and employing evolutionary game theory and agent-based modeling, efficient methods for maximizing interests through MSs' cooperation can be developed.
Article
Mathematics
Chanjuan Liu, Jinmiao Cong, Tianhao Zhao, Enqiang Zhu
Summary: In intelligent systems, modeling and predicting the strategies and behaviors of other agents is crucial. We propose a framework that incorporates opponent modeling into reinforcement learning to improve the decision payoff of the primary agent. Experimental results show that this approach effectively enhances decision outcomes.
Article
Computer Science, Artificial Intelligence
Mu Li, Kai Zhang, Jinxing Li, Wangmeng Zuo, Radu Timofte, David Zhang
Summary: This method proposes a context-based nonlocal attention block for entropy modeling in image compression. The experiments demonstrate its superiority in entropy modeling and low distortion situations.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
