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IEEE International Conference on Big Data

作者： Cameron Trotter Nick Wright A. Stephen McGough Matt Sharpe Barbara Cheney Mònica Arso Civil Reny Tyson Moore Jason Allen Per Berggren School of Engineering Newcastle University UK School of Computing Newcastle University UK School of Natural & Environmental Sciences Newcastle University UK School of Biological Sciences University of Aberdeen UK School of Biology University of St Andrews UK Chicago Zoological Society’s Sarasota Dolphin Research Program Sarasota FL USA

ISBN: (纸本)9781665480468

Photo-identification (photo-id) is one of the main non-invasive capture-recapture methods utilised by marine researchers for monitoring cetacean (dolphin, whale, and porpoise) populations. This method has historically been performed manually resulting in high workload and cost due to the vast number of images collected. Recently automated aids have been developed to help speed-up photo-id, although they are often disjoint in their processing and do not utilise all available identifying information. Work presented in this paper aims to create a fully automatic photo-id aid capable of providing most likely matches based on all available information without the need for data pre-processing such as cropping. This is achieved through a pipeline of computer vision models and post-processing techniques aimed at detecting cetaceans in unedited field imagery before passing them downstream for individual level catalogue matching. The system is capable of handling previously uncatalogued individuals and flagging these for investigation thanks to catalogue similarity comparison. We evaluate the system against multiple real-life photo-id catalogues, achieving mAP@IOU[0.5] = 0.91, 0.96 for the task of dorsal fin detection on catalogues from Tanzania and the UK respectively and 83.1, 97.5% top-10 accuracy for the task of individual classification on catalogues from the UK and USA.

关键词： Computer vision Computational modeling Biological system modeling Pipelines Sociology Whales Big Data

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The sustainability of Batik tulis lasem through participatory rural appraisal (PRA) in the new motif design

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AIP Conference Proceedings 2023年第1期2594卷

作者： V. J. Basiroen I. B. K. Manuaba Graphic Design & New Media Program Visual Communication Design Department BINUS Northumbria School of Design Bina Nusantara University Jakarta Indonesia 11480 Computer Science Program Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480

Research activities carried out by researchers took place in Jeruk and Karas Kepoh Village, Pancur District, Rembang. Batik Tulis Lasem is the embodiment of the Javanese-Chinese cultural acculturation, which supports the socio-economic life of the Lasem community. Batik Lasem, which is part of the nation's cultural heritage, is currently experiencing a crisis period because there are no new designs that can attract young generation interest in this batik art. The decline in the interest of the younger generation to Batik Lasem raises two critical problems: the difficulty of regenerating Lasem entrepreneurs and the human resources of batik artisans who can produce batik motifs, and there is a threat of extinction Batik Lasem in the future. For this reason, genuine efforts are needed to design a sustainable design for Batik Lasem through the creation of new motifs. In the implementation of this research, the Participatory Rural Appraisal (PRA) method was used to act as facilitators to increase the competence of the artisans in the design motifs training, to produce new Batik Lasem motifs as a sustainable design and favored by the younger generation. At the end of this training, artisans in the two villages have successfully created sixteen batik cloth with new motifs based on local culture without losing the originality and characteristics of Batik Lasem. It is hoped that the new motif can become a new attraction and energy and a sustainable design in the life of the Batik Tulis Lasem industry.

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Mathematical modelling and optimization of parameters for Al-Si-Fe aluminum alloy reinforced by Al 2 O 3 and graphite particles using Taguchi method

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Materials Today: Proceedings 2021年 44卷 979-986页

作者： Robale Dinsa Daba Devendra Kumar Sinha Habtamu Beri Satyam Shivam Gautam Gulam Mohammed Sayeed Ahmed Ram Sewak Singh Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering ASTU ADAMA Ethiopia Department of Mechanical Engineering North Eastern Regional Institute of Science and Technology Itanagar India Department of Electronics and Communication School of Electrical Engineering and Computing ASTU ADAMA Ethiopia

In the present scenario the aluminum and its alloys are preferred due to requirement of lightweight high strength material. The present research article interrogates experimentally the study of actual density and porosity using powder metallurgy method. The experimental design is done using Taguchi L 16 orthogonal array. Actual density and porosity has been analyzed based on ‘smaller is best’ basis. Actual density and porosity are calculated using Archimedes principle. The leverage of four levels and five process parameters such as weight percentage of Al 2 O 3 , weight percentage of graphite, compaction pressure, compaction time and milling time are considered. Results reveal that Al 2 O 3 weight percentage has the highest leverage on density followed by compaction time and graphite weight percentage.

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programming Variational Quantum Circuits with Quantum-Train Agent

Programming Variational Quantum Circuits with Quantum-Train ...

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Quantum Communications, Networking, and computing (QCNC), International Conference on

作者： Chen-Yu Liu Samuel Yen-Chi Chen Kuan-Cheng Chen Wei-Jia Huang Yen-Jui Chang Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Hon Hai (Foxconn) Research Institute Taipei Taiwan Wells Fargo New York NY USA Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.

关键词： Quantum system Accuracy Computational modeling Qubit Neural networks programming Predictive models Quantum circuit Physics Long short term memory

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Efficient Hardware Design for the AV1 CDEF Filter Targeting 4K UHD Videos

Efficient Hardware Design for the AV1 CDEF Filter Targeting ...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Eduardo Zummach Roberta Palau Jones Goebel Daniel Palomino Luciano Agostini Marcelo Porto Postgraduate Program in Computing - PPGC Video Technology Research Group - ViTech Federal University of Pelotas - UFPEL Brazil

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Developed by the AOMedia industry consortium, the AOM Video 1 (AV1) is an open-source and royalty-free video encoder released in June 2018. The Constrained Directional Enhancement Filter (CDEF) is one of the three AV1 in-loop filters and it is the focus of this work. The CDEF has the goal to reduce ringing artifacts generated with the encoding process, acting as a directional deringing filter. This paper presents a hardware design for the AV1 CDEF targeting real-time processing of 4K Ultra High Definition (UHD) videos. The architecture was synthesized to ASIC using the 40nm TSMC library, requiring 185 kgates and with a power dissipation of 43 mW when running at 93 MHz, reaching the frame rate of 60 frames per second (fps). To the best of the author's knowledge, there is no other work in the literature with dedicated hardware design for the AV1 CDEF.

关键词： Videos Hardware FCC Decoding Damping Industries Encoding

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Invisible Dynamic Mechanic Adjustment in Virtual Reality Games

Invisible Dynamic Mechanic Adjustment in Virtual Reality Gam...

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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Justus Robertson Rogelio E. Cardona-Rivera R. Michael Young University of York York UK School of Computing and the Entertainment Arts and Engineering Program University of Utah UT USA

ISBN: (数字)9781728174631

ISBN: (纸本)9781728174648

A key part of managing a player's virtual reality experience is ensuring that the environment behaves consistently to the player's interaction. In some instances, however, it is important to change how the world behaves-i.e. the world's simulation rules or mechanics-because doing so preserves the virtual environment's intended quality. Mechanics changes must be done carefully; if too overt, they may be perceivable and potentially thwart a player's sense of presence or *** paper reports the result of a study, which demonstrates the widely-held but heretofore-untested belief that changing an environment's mechanics without considering what the player knows is visible to the player. The study's findings motivate the paper's second contribution: an automated method to perform invisible dynamic mechanics adjustment, which affords shifting a game's previously-established mechanics in a manner that is not perceivably inconsistent to players. This method depends on a knowledge-tracking strategy and two such strategies are presented: (1) a conservative one, relevant to a wide variety of virtual environments, and (2) a more nuanced one, relevant to environments that will be experienced via head-mounted virtual reality displays. The paper concludes with a variety of design-centered considerations for the use of this artificial intelligence system within virtual reality.

关键词： Wounds Games Oils Solid modeling Virtual environments Artificial intelligence Tutorials

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Binary-coupling sparse Sachdev-Ye-Kitaev model: An improved model of quantum chaos and holography

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Physical Review B 2023年第8期107卷 L081103-L081103页

作者： Masaki Tezuka Onur Oktay Enrico Rinaldi Masanori Hanada Franco Nori Department of Physics Kyoto University Kitashirakawa Sakyo-ku Kyoto 606-8502 Japan Department of Mathematics University of Surrey Guildford Surrey GU2 7XH United Kingdom Physics Department University of Michigan Ann Arbor Michigan 48109 USA Theoretical Quantum Physics Laboratory Cluster of Pioneering Research RIKEN Wako Saitama 351-0198 Japan Interdisciplinary Theoretical & Mathematical Science Program (iTHEMS) RIKEN Wako Saitama 351-0198 Japan Center for Quantum Computing (RQC) RIKEN Wako Saitama 351-0198 Japan

The sparse version of the Sachdev-Ye-Kitaev (SYK) model reproduces essential features of the original SYK model while reducing the number of disorder parameters. In this Research Letter, we propose a further simplification of the model which we call the binary-coupling sparse SYK model. We set the nonzero couplings to be ±1, rather than being sampled from a continuous distribution such as Gaussian. Remarkably, this simplification turns out to be an improvement: The binary-coupling model exhibits strong correlations in the spectrum, which is the important feature of the original SYK model that leads to the quick onset of the random-matrix universality, more efficiently in terms of the number of nonzero terms. This model is better suited for analog or digital quantum simulations of quantum chaotic behavior and holographic metals due to its simplicity and scaling properties.

关键词： Majorana fermions Quantum chaos Quantum gravity 0-dimensional systems Quantum many-body systems Random graphs Strongly correlated systems Exact diagonalization Random matrix theory Sachdev-Ye-Kitaev model

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Machine Learning Approach to Predicting Tunnel Field-Effect Transistors

Machine Learning Approach to Predicting Tunnel Field-Effect ...

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International Symposium on VLSI Technology, Systems and Applications

作者： Chandni Akbar Narasimhulu Thoti Yiming Li Paralllel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu Taiwan EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Paralllel and Scientific Computing Laboratory EECS International Graduate Program Institue of Communications Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan National Yang Ming Chiao Tung University Hsinchu Taiwan Institue of Communications Engineering National Chiao Tung University Hsinchu Taiwan

We for the first time investigate the possibility to replace the device simulation for tunnel field-effect transistors (TFETs) with a machine learning (ML) algorithm. By incorporating the experimentally validated device simulation, a keyML technique named random forest regression (RFR) model is advanced and applied to predict characteristics of TFETs. The results of this work may benefit the design and fabrication of TFETs based on the well-trained RFR model. Very fast and accurate drain current (ID) prediction in terms of the engineering acceptable root-mean-square (RMSE) error inaugurates TFET technology with ML with a potential application to significantly reduce the computational cost.

关键词： Training TFETs Machine learning algorithms Computational modeling Vegetation Predictive models Data models

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Predicting Neurological Outcomes of Comatose Cardiac Arrest Patients Using Transformer Neural Networks with EEG Data

Predicting Neurological Outcomes of Comatose Cardiac Arrest ...

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Computers in Cardiology (CinC)

作者： Jefferson Dionisio Che Lin Lian-Yu Lin Wen-Chau Wu Smart Medicine and Health Informatics Program National Taiwan University (NTU) Taipei Taiwan Department of Electrical Engineering NTU Graduate Institute of Communication Engineering NTU School of Medicine NTU Center for Advanced Computing and Imaging in Biomedicine NTU Center for Biotechnology NTU Department of Internal Medicine NTU Hospital Taipei Taiwan Institute of Medical Device and Imaging NTU Department of Radiology College of Medicine NTU Graduate Institute of Clinical Medicine NTU

As part of the 2023 PhysioNet Challenge, our team FINDING_MEMO utilized Transformer to predict outcomes using patient EEG data since it excels at dealing with sequential data like EEG. We mainly used the Transformer encoder block's multi-head self-attention to generate representations from the input and leverage several hidden layers to form the final prediction. Using the latest EEG from every patient, our team achieved the challenge score of 0.42 with the hidden validation set (ranked 36th out of 73 invited teams) and obtained a result of 0.37 (ranked 29th out of 36 qualified teams). Our results show a consistent performance across varying EEG recording durations in both the validation and test set. Our team also had the second-best score when evaluated, with only 12 hours of available recordings in the test set. Such promising results showcase the models' generalizability and clinical potential in predicting outcomes for comatose patients, especially for limited available EEG recordings.

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Learning interface conditions in domain decomposition solvers 22

Learning interface conditions in domain decomposition solver...

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Ali Taghibakhshi Nicolas Nytko Tareq Zaman Scott MacLachlan Luke Olson Matthew West Mechanical Science and Engineering University of Illinois Urbana-Champaign Urbana IL Computer Science University of Illinois Urbana-Champaign Urbana IL Scientific Computing Program Memorial University of Newfoundland and Labrador St. John's NL Canada Mathematics and Statistics Memorial University of Newfoundland and Labrador St. John's NL Canada

ISBN: (纸本)9781713871088

Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations. Yet the optimal construction of these methods requires tedious analysis and is often available only in simplified, structured-grid settings, limiting their use for more complex problems. In this work, we generalize optimized Schwarz domain decomposition methods to unstructured-grid problems, using Graph Convolutional Neural Networks (GCNNs) and unsupervised learning to learn optimal modifications at subdomain interfaces. A key ingredient in our approach is an improved loss function, enabling effective training on relatively small problems, but robust performance on arbitrarily large problems, with computational cost linear in problem size. The performance of the learned linear solvers is compared with both classical and optimized domain decomposition algorithms, for both structured- and unstructured-grid problems.

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