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International Conference on Neural Information Processing

作者： S. Morokami A. Suemitsu M. Morita Doctoral Program in System Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Doctoral Program in Engineering University of Tsukuba Tsukuba Ibaraki Japan Institute of Engineering Mechanics and Systems University of Tsukuba Tsukuba Ibaraki Japan

In the delayed match-to-sample task, responses of inferior temporal neurons to adjacent stimuli in the sequence are correlated to each other when the monkey was trained repeatedly with the sequence of visual stimuli, although the monkey was not required to associate the stimuli with each other. This correlation, however, is not observed for a monkey with lesions of the rhinal cortex, which is not consistently explained by existing models of such correlated responses. In the present study, we construct a model consisting of two networks corresponding to area TE and the perirhinal cortex, and show that perirhinal plasticity may underlie the mechanism of implicit association learning.

关键词： Brain modeling Neurons systems engineering and theory Lesions Tellurium Fractals Testing Delay effects

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Top-down and bottom-up processing of spatiotemporal patterns in a fully recurrent network of nonmonotonic neurons

Top-down and bottom-up processing of spatiotemporal patterns...

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International Conference on Neural Information Processing

作者： S. Murakami M. Morita Doctoral Program in Engineering University of Tsukuba Ibaraki Japan Institute of Engineering Mechanics and Systems University of Tsukuba Ibaraki Japan

A fully recurrent neural network with a nonmonotonic activation function that treats temporal sequences without expanding them into spatial patterns is described. This network associates a complex spatiotemporal pattern with a simple one using trajectory attractors formed by simple learning. Computer simulations show that the model not only has high recognition and generation abilities but can also perform advanced processing using bidirectional interactions.

关键词： Spatiotemporal phenomena Intelligent networks Neurons Recurrent neural networks Biological neural networks Pattern recognition systems engineering and theory Computer simulation Neural networks Delay

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Development of a Hybrid Actuation Hand Exoskeleton with Redundant Compliant Mechanisms 16

Development of a Hybrid Actuation Hand Exoskeleton with Redu...

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16th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Shu, Bairui Sun, Zhenyu Zhang, Xinyu Yokoi, Hiroshi Jing, Xiaobei Li, Guanglin Yong, Xu The Siat Branch Shenzhen518055 China The University of Electro-Communications Department of Mechanical Engineering and Intelligent Systems Tokyo182-8585 Japan The University of Electro-Communications Joint Doctoral Program for Sustainability Research Tokyo182-8585 Japan

ISBN: (纸本)9798350330755

Exoskeleton robots are currently widely used in the field of rehabilitation medicine to effectively assist patients with hand function loss in their rehabilitation training. To accommodate the physiological characteristics of the hand, particularly the deviation of the joint rotation axis, this paper proposes a hybrid-driven hand exoskeleton system with redundant compliant mechanisms and conducts motion and force analysis on it. The exoskeleton system can independently drive three fingers and drive their joints separately. To verify whether the exoskeleton system meets the rehabilitation requirements, angle verification experiments and object grasping experiments were conducted. The results showed that the maximum joint range of motion of the exoskeleton system reached 66 °, with an average joint range of motion of 55 ° , fully meeting the rehabilitation needs. © 2023 IEEE.

关键词： Patient rehabilitation

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Artificial intelligence for modelling infectious disease epidemics

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Nature 2025年第8051期638卷 623-635页

作者： Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. © Springer Nature Limited 2025.

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Using Entropy for Modeling Difficulty in the Asteroid Escape Sliding Puzzle

Using Entropy for Modeling Difficulty in the Asteroid Escape...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Jose A. del Solar-Zavala Hans Schaa Nicolas A. Barriga Doctoral Program in Engineering Systems Universidad de Talca Curicó Chile Faculty of Engineering Universidad de Talca Talca Chile

Developing a standarized metric for difficulty that can be applied to a large number of puzzles is not trivial. This does not come as a surprise because of the subjective factors involved in defining difficulty. However, studies that address the design and application of metrics that can be applied to multiple games are still important, because they can still be used to increase the quality of content generated by automated agents. We take a look at applying information entropy concepts in the game Asteroid Escape and compare the results with other metrics to assess difficulty used in games of similar characteristics. This approach is largely based on future work proposal from a previous study done on The Witness puzzles that yielded positive results on using an automatic method to assess the difficulty of user rated puzzles. This study also includes a modification of BFS and A* capable of finding every shortest solution. From the implementation, it is possible to look at contradicting results with the literature, where basic metrics had a better result correlating with an official definition of difficulty from the game designers. The impact expected from this study is to propose an update to the the corpus of puzzle games where the uncertainty metric for difficulty has been applied. As having an accurate assessment of difficulty can open the doors to other studies, such as improving the quality of the output from procedural content generation methods in games or propose an automated method of difficulty adjustment based on this metric.

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Assessment of Factors Influencing Agricultural Transformation Process: Evidence from Midhills Region of Nepal

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Asia-Pacific Journal of Rural Development 2000年第1期10卷 1 - 25页

作者： Surendra B. Thapa Ganesh P. Shivakoti Doctoral student and Visiting Faculty Agricultural & Aquatic Systems and Engineering Program School of Environment Resources and Development Asian Institute of Technology Thailand respectively.

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Study on the quench behaviour of molten fuel material jetted into coolant

Nihon Kikai Gakkai Ronbunshu, B Hen/Transactions of the Japa...

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Nihon Kikai Gakkai Ronbunshu, B Hen/Transactions of the Japan Society of Mechanical Engineers, Part B 2005年第703期71卷 947-953页

作者： Abe, Yutaka Kizu, Tetsuya Nariai, Hideki Chitose, Keiko Koyama, Kazuya Doctoral Program in Engineering Mechanics and Energy Graduate School of Systems and Information Engineering 1-1-1 Tennodai Tsukuba-shi Ibaraki 305-8573 Japan

In a core disruptive accident (CDA) of a Fast Breeder Reactor, the post accident heat removal (PAHR) is crucial for the accident mitigation. The molten core material should be solidified in the sodium coolant in the reactor vessel. In the present experiment, molten material is injected into water to experimentally obtain fragments and the visualized information of the fragmentation. The distributed particle behaviour of the molten material jet is observed with high-speed video camera. The distributions of the fragmented droplet diameter from the molten material jet are evaluated by correcting the solidified particles. The experimental results of the mean fragmented droplet diameter are compared with the existing theories. Consequently, the fragmented droplet diameter is close to the value estimated based on the Kelvin-Helmholtz instability. Once the particle diameter of the fragmented molten,material could be known from a hydrodynamic model, it becomes possible to estimate the mass ratio of the molten particle to the total injected mass by combining an appropriate heat transfer model The mass ratio of the molten fragment to total mass of the melted mixed oxide fuel in sodium coolant estimated in the present study is very small. The result means that most of the molten mixed oxide fuel material injected into the sodium coolant can be cooled down under the solidified temperature, if the amount of the coolant is sufficient.

关键词： Breeder reactors

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Evaluating Standard Search Enhancements Performance in Zen Puzzle Garden

Evaluating Standard Search Enhancements Performance in Zen P...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Hans Schaa Jose A. del Solar-Zavala Nicolas A. Barriga Doctoral Program in Engineering Systems Universidad de Talca Curicò Chile Faculty of Engineering Universidad de Talca Talca Chile

Sokoban-type puzzles and their variants involve complex planning and decision-making challenges in wide and deep search spaces. Such scenarios are interesting for testing path-planning algorithms. This document uses A * and IDA * (Iterative Deepening A *) algorithms to solve Zen Puzzle Garden game boards; a Sokoban-type puzzle where you need rake the sandy area completely. The algorithms are evaluated in terms of speed and node expansion in moderately complex boards. Additionally, we implement three improvements: transposition tables, move ordering, and deadlock tables. The results show that IDA * with the three proposed improvements is on average faster than A *. Although its strength is its low memory usage, it can be seen that it is very competitive versus A * in terms of time usage. Transposition tables and deadlocks tables reduce by 500 times the number of nodes expanded by the IDA * without improvements. On the other hand, the ordering of nodes is not very effective for some boards, which causes a worse performance of the IDA * algorithm, giving rise to greater exploration in boards that do not lead to the solution. Studying these algorithms can be beneficial in the field of path-finding for Sokoban-type game domains or solver-based procedural content generators.

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Power assist control for leg with HAL-3 based on virtual torque and impedance adjustment

Power assist control for leg with HAL-3 based on virtual tor...

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IEEE International Conference on systems, Man and Cybernetics

作者： S. Lee Y. Sankai Doctoral Program of System and Information Engineering University of Tsukuba Japan Institute of Systems and Engineering Mechanics University of Tsukuba Ibaraki Japan

This paper describes a method of power assist control for lower body based on neuromuscular signal, s-EMG (surface ElectroMyogram/Myoelectricity), and impedance adjustment around knee joint with the assist system, HAL (Hybrid Assistive Leg) -3 we have developed. Virtual Torque calculated by s-EMG enabled the HAL-3 to be operated as to intention of the experimental subject put on HAL, and assist the motion of lower body by predicting the moment around joints. Besides, the operator was able to swing the leg lighter by reducing the inertia and viscous friction around joint of the subject and HAL-3. In order to verify the proposed method, experiments for simple motion was performed with impedance values found by parameter identification with RLS (Recursive Least Square) method. The evaluation of assisted motion was done by Assist Efficiency (AE) calculated from s-EMG in nearly proportion to the operator's muscle force. The results showed the response of operational signal into actuator with impedance adjustment was improved dramatically, and the amplitudes of s-EMG were reduced significantly, then we could confirm the availability of impedance adjustment.

关键词： Torque control Leg Surface impedance Control systems Neuromuscular Knee Friction Parameter estimation Resonance light scattering Least squares methods

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Predicting Solvability and Difficulty of Sokoban Puzzles

Predicting Solvability and Difficulty of Sokoban Puzzles

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Computer Science Society (SCCC) International Conference Chilean

作者： Hans Schaa Jose A. Del Solar-Zavala Nicolas A. Barriga Doctoral Program in Engineering Systems Universidad de Talca Curicó Chile Faculty of Engineering Universidad de Talca Talca Chile

ISBN: (数字)9798331527891

ISBN: (纸本)9798331527907

Knowing if a Sokoban level has a solution requires a high investment of computational resources. This also happens when estimating difficulty; heuristics may not be precise, only work for simplified cases, be discontinuous and take much computing time. The calculation of high-fidelity heuristics is expensive and the performance of optimization systems is reduced by the time they take to deliver the result. In this article, two Convolutional Neural Networks (CNN) are implemented, a classifier of resolvable Sokoban boards and a regressor that predicts the number of pushes necessary to solve them. These obtained an accuracy of 79 % and MAE of 28, respectively. Trained models are useful in systems that do not require optimality, but rather guidance within the search space that balances time and quality. These networks can be used as surrogate methods, replacing high-fidelity heuristics that take too long.

关键词： Computer science Accuracy Convolutional neural networks Optimization Investment

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