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61st Annual Meeting of the Association for Computational Linguistics, ACL 2023

作者： Yandan, Zheng Anran, Hao Tuan, Luu Anh School of Computer Science and Engineering Interdisciplinary Graduate Program-HealthTech Nanyang Technological University Singapore

ISBN: (纸本)9781959429722

Semi-supervised learning has been an important approach to address challenges in extracting entities and relations from limited data. However, current semi-supervised works handle the two tasks (i.e., Named Entity Recognition and Relation Extraction) separately and ignore the cross-correlation of entity and relation instances as well as the existence of similar instances across unlabeled data. To alleviate the issues, we propose Jointprop, a Heterogeneous Graph-based Propagation framework for joint semi-supervised entity and relation extraction, which captures the global structure information between individual tasks and exploits interactions within unlabeled data. Specifically, we construct a unified span-based heterogeneous graph from entity and relation candidates and propagate class labels based on confidence scores. We then employ a propagation learning scheme to leverage the affinities between labelled and unlabeled samples. Experiments on benchmark datasets show that our framework outperforms the state-of-the-art semi-supervised approaches on NER and RE tasks. We show that the joint semi-supervised learning of the two tasks benefits from their codependency and validates the importance of utilizing the shared information between unlabeled data. © 2023 Association for Computational Linguistics.

关键词： Extraction

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A two-stage deep learning-based hybrid model for daily wind speed forecasting

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Heliyon 2025年第1期11卷 e41026页

作者： Band, Shahab S. Ameri, Rasoul Qasem, Sultan Noman Mehdizadeh, Saeid Gupta, Brij B. Pai, Hao-Ting Shahmirzadi, Danyal Salwana, Ely Mosavi, Amir Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Douliu Taiwan Computer Science Department College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11432 Saudi Arabia Computer Science Department Faculty of Applied Science Taiz University Taiz 6803 Yemen Water Engineering Department Urmia University Urmia Iran Department of Computer Science and Information Engineering Asia University Taichung 413 Taiwan Symbiosis Centre for Information Technology (SCIT) Symbiosis International University Pune India Center for Interdisciplinary Research University of Petroleum and Energy Studies (UPES) Dehradun India Department of Big Data Business Analytics National Pingtung University Pingtung Taiwan of Engineering Science and Technology National Yunlin University of Science and Technology 123 University Road Yunlin Douliou 64002 Taiwan Institute of Visual Informatics Universiti Kebangsaan Malaysia Selangor Bangi 43600 Malaysia John von Neumann Faculty of Informatics Obuda University Budapest Hungary Ludovika University of Public Service Budapest Hungary

Global adoption of wind energy continues to increase, while improving the efficiency of turbine settings requires reliable wind speed (WS) models. The latest models rely on artificial intelligence (AI) optimizations which constructs tests on a range of novel hybrid models to examine the reliability. Gradient Boosting (GB), Random Forest (RF), and Long Short-Term Memory (LSTM) are used in new combinations for data pre-processing. A Time Varying Filter-based Empirical Mode Decomposition (TVFEMD) model is coupled with the GB and LSTM standalone models, to create TVFEMD-GB and TVFEMD-LSTM hybrids, which are run in competition with each other. Eventually, a preferred hybrid form is established, simultaneous hybridization of TVFEMD with GB and LSTM. This study is the first to hybridize these fundamental systems, and create a TVFEMD-GB-LSTM model that can forecast WS. This study finds that the novel hybrid models exhibit superior performance to standalone GB and LSTM models, opening the pathway to alternative WS prediction techniques. © 2024 The Authors

关键词： Artificial intelligence Big data Data science Forecasting Gradient boosting Long short-term memory Machine learning Wind speed

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Perceptual and linguistic category formation in infants

Perceptual and linguistic category formation in infants

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9th European Conference on Speech Communication and Technology

作者： Sudo, Tamami Mogi, Ken Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Sony Computer Science Laboratories Inc.

It is known that infants are aware of the category of objects in daily life before explicit vocabulary acquisition starts. It has been suggested that the ability of categorization is likely to play an essential role in its overall cognitive development. In this study, we conducted a series of experiments using stimuli that have various attributes in order to understand the process of such a categorization in an infant's pre-linguistic development. We consider two possible cognitive processes of linguistic categorization. One possible scenario is that certain members of the categories are derived from similarity with the most representative members of a category (prototypical members). Alternatively, the coupling of each category member-ship with relevant labels can be traced to the symbol grounding problem. Our results are consistent with an interpretation that the cortical systems involved in language development is inseparably linked with prototype effects in categorization.

关键词： Speech analysis

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FedCFC: On-Device Personalized Federated Learning with Closed-Form Continuous-Time Neural Networks 23

FedCFC: On-Device Personalized Federated Learning with Close...

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23rd ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2024

作者： Dai, Yimin Tan, Rui Nanyang Technological University Interdisciplinary Graduate School Singapore Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798350362015

Closed-form continuous-time (CFC) neural networks have superior expressivity in modeling time series data compared with recurrent neural networks. CFC's lower training and inference overheads also make it appealing for microcontroller-based platforms. This paper proposes FedCFC, which advances CFC from the centralized learning setting to the federated learning paradigm. FedCFC features a novel and communication-efficient aggregation strategy to address the problem of class distribution skews across clients' training data. The strategy is designed based on a new empirical property of CFC identified in this paper, i.e., involatility of a sub-network of CFC with respect to training data's class distribution. Extensive evaluation based on multiple time series datasets shows that FedCFC achieves higher or similar accuracy with 7.6× to 11× reduction in communication overhead, compared with recent federated learning approaches designed to address the class distribution skew problem. Implementations of FedCFC on four microcontroller platforms show its portability to low-end computing devices with 256kB memory and even less. © 2024 IEEE.

关键词： Edge computing

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Computation-Efficient Model Predictive Control of a Multilevel Current Source Converter 49

Computation-Efficient Model Predictive Control of a Multilev...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Chen, Muyu Yuan, Zhige Ghias, Amer M. Y. M. Nicholas, Vun Chan Hua School of Electrical and Electronic Engineering Collab. Initiative Interdisciplinary Graduate Programme Nanyang Technological University Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350331820

This paper presents a modified finite control set model predictive control (FCS-MPC) that can significantly reduce computation time and maintain good quality of output voltage. The switching states of a three-phase five-level current source converter (5L-CSC) are sorted according to the corresponding output converter current level. The influences of every switching state on the converter inductor current are analyzed. Then the optimal switching state can be anchored based on the converter current level that minimizes the cost function and converter inductor current conditions. The proposed method eliminates the need for the discrete-time model establishment for the converter. It avoids the ergodic search through all switching states, easing the controller's computation burden. Besides, this algorithm achieves multiple control goals without assigning different weighting factors to various control objectives. The simulated output voltage total harmonics distortion (THD), the inductor current ripple, and the execution time of the modified model predictive control and traditional model predictive control are compared to validate the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Model predictive control

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ON THE SECURITY OF HMM-BASED SPEAKER VERIFICATION SYSTEMS AGAINST IMPOSTURE USING SYNTHETIC SPEECH 6

ON THE SECURITY OF HMM-BASED SPEAKER VERIFICATION SYSTEMS AG...

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6th European Conference on Speech Communication and Technology, EUROSPEECH 1999

作者： Masuko, Takashi Hitotsumatsu, Takafumi Tokuda, Keiichi Kobayashi, Takao Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Japan Department of Computer Science Nagoya Institute of Technology Japan

For speaker verification systems, security against imposture is one of the most important problems, and many approaches to reducing false acceptance of impostors as well as false rejection of clients have been investigated. On the other hand, imposture using synthetic speech has not been considered. In this paper, we investigate imposture against speaker verification systems using synthetic speech. We use an HMM-based text-prompted speaker verification system with a false acceptance rate of 0% for human impostors as a reference system, and adopt a trainable HMM-based speech synthesis system for imposture. Experimental results show that false acceptance rates for synthetic speech reached over 70% by training the synthesis system using only 1 sentence from each customer, and current security of HMM-based speaker verification systems against synthetic speech is inadequate. © 1999 6th European Conference on Speech Communication and Technology, EUROSPEECH 1999. All rights reserved.

关键词： Speech synthesis

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Regression analyses between physiological indexes and level of understanding with VAS of a listening task 5

Regression analyses between physiological indexes and level ...

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5th International Conference on Physiological Computing Systems, PhyCS 2018

作者： Omata, Masaki Nakazawa, Kazuya Interdisciplinary Graduate School University of Yamanashi Kofu Japan Department of Computer Science and Engineering University of Yamanashi Kofu Japan

ISBN: (纸本)9789897583292

This paper describes logistic regression analyses and multiple regression analyses to explain relationships between physiological signals and subjective self-reported levels of understanding of a second language listening task by using a visual analog scale (VAS) of 999 degrees. Mean contribution ratio of the logistic regression expressions was 0.72, and mean contribution ratio of the multiple regression expressions was 0.70. Power value of theta band of brain waves has a certain tendency to change according to the level of understanding. Accuracy of the regression expressions using VAS was the same or more than that of the four-level scale as our previous work. © 2018 by SCITEPRESS - science and Technology Publications, Lda. All rights reserved.

关键词： Regression analysis

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Improving feedback to novice learners on constructing i∗ requirements diagrams 6

Improving feedback to novice learners on constructing i∗ re...

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2016 6th International Workshop on computer science and engineering, WCSE 2016

作者： Mejri, Hajer Kawamoto, Pauline N. Interdisciplinary Graduate School of Science and Technology Shinshu University Nagano Japan Department of Computer Science and Engineering Shinshu University Nagano Japan

ISBN: (纸本)9789811100086

Although a number of free computer-aided tools are available to help users construct requirements models according to the prescribed design rules of the i∗ modelling language, none of the tools surveyed thus far provided a full set of syntax checking features. To cover this gap in the current i∗ tools landscape, we are developing a web-based system called i∗Check to complement the available tools and offer users automatic on-demand feedback on the syntactical quality of their diagram designs. In this work, we use i∗Check to explore how different kinds of feedback can help the beginner recognize design mistakes at an early stage in learning. By asking new learners to debug a series of i∗ diagrams, we investigated the effectiveness of our tool in guiding them to locate and correct defects in given designs compared to some existing tools' checking features. We aimed to determine the factors that contribute to the success or failure of our solution. Based on experimental observations we noticed that i) the usage of i∗Check seems to lead to a good overall score and ii) this tool bears potential for improvement especially making it more concise in locating where in a diagram the defects appear.

关键词： Modeling languages

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Prototype of multi-layer personal cardiac monitoring system for data interoperability problem 20

Prototype of multi-layer personal cardiac monitoring system ...

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5th International Conference on Sustainable Information engineering and Technology, SIET 2020

作者： Pramukantoro, Eko Sakti Gofuku, Akio Graduate School of Interdisciplinary Science and Engineering in Health Systems Okayama University Japan Faculty of Computer Science University of Brawijaya Malang Indonesia

ISBN: (纸本)9781450376051

Personal monitoring of heart conditions offers an advantage as a prevention mechanism for cardiovascular disease. This system can be developed using a wearable sensor device along with IoT approach. However, the data interoperability problem often arises in attempt to develop an IoT-based system. Data interoperability comes from different data formats to save the data that are produced by health sensor devices. The current solution can be either cloud or edge-based middleware which both have their own merits and drawbacks. This study offers multi-layer monitoring heart conditions that combines cloud and edge-based middleware to solve data interoperability. The middleware on the edge layer performs data normalization using the JSON format and Restful API standard to transfer data to communicate with an IoT application. On the other hand, at the cloud side, it provides heterogeneous data storage with the ability to store various health data formats. © 2020 ACM.

关键词： Middleware

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Graphs representing quadtree structures using eight edges

Graphs representing quadtree structures using eight edges

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4th International Symposium on Communications, Control, and Signal Processing, ISCCSP-2010

作者： Kadowaki, Ryosuke Motomura, Koyo Ohkura, Shinpei Aizawa, Kunio Department of Mathematics and Computer Science Interdisciplinary Graduate School of Science and Engineering Shimane University Matsue Shimane 690-8504 Japan Department of Mathematics and Computer Science Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Shimane 690-8504 Japan

ISBN: (纸本)9781424462858

Quadtree [1] is an important data structure for image processing. In this paper, a graph based data structure is proposed for representing two-dimensional binary images. This data structure uses eight edges for each node to represent neighborhood relations in quadtrees. New neighbor finding and connected component labeling algorithms using the structure are also introduced. Empirical tests are given for the algorithms in comparison with usual neighbor finding and connected component labeling algorithm based on quadtrees [2]-[3]. In our experiments using natural images, the proposed neighbor finding algorithm is more than twice as fast as algorithm using quadtrees and the proposed connected component labeling algorithm is 40% faster than quadtree based algorithm. ©2010 IEEE.

关键词： Graphic methods

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