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International Symposium on Chinese Spoken Language Processing

作者： Kun-Yi Huang Chung-Hsien Wu Qian-Bei Hong Ming-Hsiang Su Yuan-Rong Zeng Department of Computer Science and Information Engineering National Cheng Kung University Taiwan PhD Program for Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Taiwan

ISBN: (纸本)9781538656280;9781538656273

A complete emotional expression typically contains a complex temporal course in a natural conversation. Related research on utterance-level, segment-level and multi-level processing lacks understanding of the underlying relation of emotional speech. In this work, a convolutional neural network (CNN) with audio word-based embedding is proposed for emotion modeling. In this study, vector quantization is first applied to convert the low level features of each speech frame into audio words using k-means algorithm. Word2vec is adopted to convert an input speech utterance into the corresponding audio word vector sequence. Finally, the audio word vector sequences of the training emotional speech data with emotion annotation are used to construct the CNN- based emotion model. The NCKU-ES database, containing seven emotion categories: happiness, boredom, anger, anxiety, sadness, surprise and disgust, was collected and five-fold cross validation was used to evaluate the performance of the proposed CNN-based method for speech emotion recognition. Experimental results show that the proposed method achieved an emotion recognition accuracy of 82.34%, improving by 8.7% compared to the Long Short Term Memory (LSTM)- based method, which faced the challenging issue of long input sequence. Comparing with raw features, the audio word-based embedding achieved an improvement of 3.4% for speech emotion recognition.

关键词： Emotion recognition Feature extraction Speech recognition Acoustics Training Databases Neural networks

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Exploring Macroscopic Fluctuation of Facial Expression for Mood Disorder Classification

Exploring Macroscopic Fluctuation of Facial Expression for M...

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Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia)

作者： Qian-Bei Hong Chung-Hsien Wu Ming-Hsiang Su Kun-Yi Huang Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Tainan Taiwan Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781538653128

In clinical diagnosis of mood disorder, a large portion of bipolar disorder patients (BDs) are misdiagnosed as unipolar depression (UDs). Clinicians have confirmed that BDs generally show "reduced affect'' during clinical treatment. Thus, it is expected to build an objective and one-time diagnosis system for diagnosis assistance by using machine-learning techniques. In this study, facial expressions of BD, UD and control group (C) elicited by emotional video clips are collected for exploring temporal fluctuation characteristics of intensities of facial muscles expression among the three groups. The differences of facial expressions among mood disorders are investigated by observing macroscopic fluctuations. To deal with these problems, the corresponding methods for feature extraction and modeling are proposed. From the viewpoint of macroscopic facial expression, action unit (AU) is applied for describing the temporal transformation of muscles. Then, modulation spectrum is used for extracting short-term variation of AU. The multilayer perceptron (MLP)-based disorder prediction model is then applied to obtain the prediction results. For evaluation of the proposed method, 12 subjects for three group are included in the K-fold (K=12) cross validation experiments. The experiment results reached 61.1% classification accuracy, and outperformed the other baseline methods.

关键词： Mood Gold Fluctuations Databases Feature extraction Modulation Predictive models

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Syncgan: Synchronize the Latent Spaces of Cross-Modal Generative Adversarial Networks

Syncgan: Synchronize the Latent Spaces of Cross-Modal Genera...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Wen-Cheng Chen Chien-Wen Chen Min-Chun Hu Dept. of Computer Science and Information Engineering National Cheng Kung University Taiwan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Taiwan

Generative adversarial network (GAN) has achieved impressive success on cross-domain generation, but it faces difficulty in cross-modal generation due to the lack of a common distribution between heterogeneous data. Most existing methods of conditional based cross-modal GANs adopt the strategy of one-directional transfer and have achieved preliminary success on text-to-image transfer. Instead of learning the transfer between different modalities, we aim to learn a synchronous latent space representing the cross-modal common concept. A novel network component named synchronizer is proposed in this work to judge whether the paired data is synchronous/corresponding or not, which can constrain the latent space of generators in the GANs. Our GAN model, named as SyncGAN, can successfully generate synchronous data (e.g., a pair of image and sound) from identical random noise. For transforming data from one modality to another, we recover the latent code by inverting the mappings of a generator and use it to generate data of different modality. In addition, the proposed model can achieve semi-supervised learning, which makes our model more flexible for practical applications.

关键词： Synchronization Gallium nitride Generators Data models Training Generative adversarial networks Training data

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LSTM-based Text Emotion Recognition Using Semantic and Emotional Word Vectors

LSTM-based Text Emotion Recognition Using Semantic and Emoti...

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Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia)

作者： Ming-Hsiang Su Chung-Hsien Wu Kun-Yi Huang Qian-Bei Hong Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Tainan Taiwan

ISBN: (纸本)9781538653128

This study proposes a long-short term memory (LSTM)-based approach to text emotion recognition based on semantic word vector and emotional word vector of the input text. For each word in an input text, the semantic word vector is extracted from the word 2vec model. Besides, each lexical word is projected to all the emotional words defined in an affective lexicon to derive an emotional word vector. An autoencoder is then adopted to obtain the bottleneck features from the emotional word vector for dimensionality reduction. The autoencoder bottleneck features are then concatenated with the features in the semantic word vector to form the final textual features for emotion recognition. Finally, given the textual feature sequence of the entire sentence, the LSTM is used for emotion recognition by modeling the contextual emotion evolution of the input text. For evaluation, the NLPCC-MHMC-TE database containing seven emotion categories: anger, boredom, disgust, anxiety, happiness, sadness, and surprise was constructed and used. Five-fold cross-validation was employed to evaluate the performance of the proposed method. Experimental results show that the proposed LSTM-based method achieved a recognition accuracy of 70.66%, improving 5.33% compared with the CNN-based method. Besides, the proposed method based on integration of the semantic word vector and emotional word vector of the input text outperformed that using the individual feature vector.

关键词： Emotion recognition Databases Logic gates Feature extraction Semantics Speech recognition Computer science

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Implementation of Mobile game for Religion Learning

Implementation of Mobile game for Religion Learning

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Edy Sulistiyo Vindy Nizirwan Anwar Diana Teresia Spits Warnars Setya Chendra Wibawa Goenawan Brotosaputro Dedy Prasetya Kristiadi Harco Leslie Hendric Spits Warnars Kiyota Hashimoto Electrical Engineering Department Universitas Negeri Surabaya Jawa Timur Indonesia Game Application & Technology Program School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Esa Unggul University Jakarta Indonesia Information Systems Department Bina Nusantara University Jakarta Indonesia Informatics Department Universitas Negeri Surabaya Jawa Timur Indonesia Information System Department Universitas Budi Luhur Jakarta Indonesia Computer Science department Raharja University Tangerang Indonesia Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Technology and Environment Prince Songkla University Phuket Campus Thailand

ISBN: (数字)9781728126654

ISBN: (纸本)9781728126661

Currently, the growth of information and technology is rapid. It makes a lot of things in various fields including education becoming more effective and efficient. In education, one of its implementation which is a game is proven to be a useful tool to support conventional teaching methods and bring a more natural understanding of learning materials. Moreover, as a product of the popular culture in modern society, video game mirrors the general culture practice in real life and reflects it via its own culture inside the game. This makes a video game can give a contribution to the social construction of reality as it affects the player's view towards learning in real life and vice versa. From there, we see that there is an opportunity for learning about religion to be supported by its utilization to provide an interactive and fun learning experience. In this paper, we discuss how a video game is implemented to support religious learning. The game was developed with the scrum method where we surveyed to gather the user requirements before the design step. The game design was made by using the use case diagram and storyboard, and it was built using Unity version 2017.3.0f3.

关键词： Games Land mobile radio Education Computer science Operating systems information systems Media

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Effects of city design on transport mode choice and exposure to health risks during and after a crisis: a retrospective observational analysis

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The Lancet Planetary Health 2025年第6期9卷 e467-e479页

作者： Kerry A Nice Jason Thompson Haifeng Zhao Sachith Seneviratne Belen Zapata-Diomedi Leandro Garcia Ruth F Hunter Rodrigo Siqueira Reis Pedro C Hallal Christopher Millett Ruoyu Wang Mark Stevenson Transport Health and Urban Systems Research Lab Faculty of Architecture Building and Planning University of Melbourne Melbourne VIC Australia Centre for Human Factors and Sociotechnical Systems University of the Sunshine Coast Buderim QLD Australia Department of Psychiatry Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Melbourne VIC Australia Healthy Liveable Cities Lab Centre for Urban Research RMIT University Melbourne VIC Australia Centre for Public Health Institute of Clinical Sciences Queen's University Belfast Belfast Northern Ireland UK Physical Activity Epidemiology Group University of São Paulo São Paulo Brazil People Health and Place Unit Prevention Research Center School of Public Health Washington University in St Louis St Louis MO USA Department of Kinesiology and Community Health University of Illinois Urbana-Champaign Champaign IL USA Postgraduate Program in Epidemiology Federal University of Pelotas Pelotas Brazil Public Health Policy Evaluation Unit School of Public Health Imperial College London London UK NOVA National School of Public Health Public Health Research Centre Comprehensive Health Research Center NOVA University Lisbon Lisbon Portugal Instituto de Estudos para Polı́ticas de Saúde São Paulo Brazil Faculty of Engineering and Information Technology and the Melbourne School of Population and Global Health University of Melbourne Melbourne VIC Australia

Background Rapid declines in city mobility during the early stages of the COVID-19 pandemic in 2020 resulted in reductions in citizens’ exposure to transport-related air pollution and associated health risks as many cities introduced non-pharmaceutical interventions designed to curb the spread of COVID-19. However, these benefits soon reversed during the pandemic's recovery phase (ie, from September, 2020, onwards), especially in cities with designs that afforded mode shifts away from public and active transport in favour of private motor vehicles. The aim of this study was to understand the association between global city designs, transport mode choices, and population-level risk exposure during 2020. Methods In this retrospective observational analysis, we assembled and analysed spatial datasets (including historical and predicted pollution levels, mobility indicators, and measures of individual disease transmission) and clustered 507 global cities using a graph neural network approach based on measures of the structural dimensions of each individual city's design and network structures of urban transportation systems. We compared city types on the basis of transportation mode shifts, air pollution levels, and associated health outcomes (ie, cardiovascular disease, ischaemic heart disease, respiratory disease, asthma, and reported COVID-19 cases) throughout 2020. We estimated risk reductions for these health outcomes across four phases of the pandemic, which we defined as the pre-pandemic, entry, mid-crisis, and recovery phases. We also identified city designs showing sustained reductions at the end of 2020 in transport-related air pollution (fine particulate matter [PM 2·5 ] and nitrogen dioxide [NO 2 ]) associated with reduced estimated risk of acute and chronic disease outcomes (ie, all-cause mortality, ischaemic heart disease mortality, cardiovascular disease, respiratory disease, and asthma). Findings The mean estimated reduction of global NO 2 concentrations

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Inventory control systems with safety stock and reorder point approach 1

Inventory control systems with safety stock and reorder poin...

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1st International Conference on information and Communications Technology, ICOIACT 2018

作者： Efrilianda, Devi Ajeng Mustafid Isnanto, R. Rizal Master Program of Information Systems School of Post Graduate Studies Diponegoro University Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Diponegoro University Semarang Central Java Indonesia Department of Computer Systems Faculty of Engineering Diponegoro University Semarang Indonesia

ISBN: (纸本)9781538609545

The inventory control systems has an important role to monitor the condition of the goods at the supply chain stage of goods distribution from the central warehouse to retail in accordance with consumer demand. The research aims to develop inventory control systems on the supply chain distribution of goods from suppliers to retail through the central warehouse with minimal supply chain costs. Minimization of supply chain cost using martingale model of forecast evaluation, and the result as the basis for calculation of safety stock and reorder point. The results of research are the system that can be used to control inventory and renewal of goods in the central warehouse by calculating the minimization of supply chain cost based on consumer demand. Case studies were conducted on the supply chain distribution of goods from the central warehouse to the retail in Semarang. The observation data derived from the goods distribution from central warehouse to retail for certain products over 4 time periods. Through such inventory control system, can minimize supply chain cost, and product inventory level can be maintained in time and amount of inventory that must be fulfilled. © 2018 IEEE.

关键词： Supply chains

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Risk based framework for assessing resilience in a complex multi-actor supply chain domain

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Supply Chain Forum 2018年第4期19卷 266-281页

作者： Ravulakollu, Anil Kumar Urciuoli, Luca Rukanova, Boriana Tan, Yao-Hua Hakvoort, Rudi A. Faulty of Technology Policy and Management Delft University of Technology Delft Netherlands Department of Industrial Economics and Management KTH Royal Institute of Technology Stockholm Sweden MIT International Logistics Program Zaragoza Logistics Center Zaragoza Spain Section Information and Communication Technology Faulty of Technology Policy and Management Technical University Delft Delft Netherlands Section Engineering Systems and Services Faulty of Technology Policy and Management Technical University Delft Delft Netherlands

Risk management frameworks offer excellent tools to identify and manage risks in supply chains. Existing tools can be used to evaluate impacts of countermeasures, however, analysts struggle with modelling how disruptions escalate in complex supply chain systems within a certain amount of time and across several stakeholders. On the contrary, the resilience discipline offers the possibility to understand how a supply chain reacts to disruptions as a function of time. Hence, this paper integrates the concepts of resilience with risk management techniques and develops a risk based resilience assessment framework in a multi-actor context. Further, the framework is operationalized by developing a computer based tool that is tested in case of fruit import in Netherlands. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： cost impact analysis multi-actor analysis resilience triangle Risk analysis risk matrix supply chain resilience

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AIRR community curation and standardised representation for immunoglobulin and T cell receptor germline sets

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Immunoinformatics (Amsterdam, Netherlands) 2023年 10卷 100025页

作者： William D Lees Scott Christley Ayelet Peres Justin T Kos Brian Corrie Duncan Ralph Felix Breden Lindsay G Cowell Gur Yaari Martin Corcoran Gunilla B Karlsson Hedestam Mats Ohlin Andrew M Collins Corey T Watson Christian E Busse Institute of Structural and Molecular Biology Birkbeck College London England. Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal. Peter O'Donnell Jr. School of Public Health UT Southwestern Medical Center Dallas TX USA. Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel. Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville KY USA. Department of Biological Sciences Simon Fraser University Burnaby BC Canada. Fred Hutchinson Cancer Research Center Seattle WA USA. Peter O'Donnell Jr. School of Public Health Department of Immunology School of Biomedical Sciences UT Southwestern Medical Center Dallas TX USA. Department of Microbiology Tumor and Cell Biology Karolinska Institutet Stockholm Swede. Department of Immunotechnology and SciLifeLab Lund University Lund Sweden. School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney NSW Australia. Division of B Cell Immunology German Cancer Research Center Heidelberg Germany.

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes. We describe interoperability standards for germline sets, and an approach to transparency based on principles of findability, accessibility, interoperability, and reusability.

关键词： AIRR-seq Immune receptor Immune receptor germline Immune receptor repertoire Rep-seq

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Hybrid Cryptography on Wireless Sensor Network: A Systematic Literature Review

Hybrid Cryptography on Wireless Sensor Network: A Systematic...

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International Conference on information Management and Technology (ICIMTech)

作者： R. Benny Gandara Gunawan Wang Ditdit Nugeraha Utama Master Program of Electrical Engineering Mereu Buana University Jakarta Indonesia Information Systems Management Department Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia

Wireless technology gradual growth in the latest years has facilitated it to bridge its applications operated extensively in many types of industry. Wireless sensor network (WSN) technology brings several benefits over traditional wired technology by reason of the lower cost, immense flexibility escalation, and scalability which is able to be obtained from the old-style one. However, in its application WSN still experience some constraints on resource limitations in the form: processor, memory and energy, and any more challenges that related to availability, reliability and security. Based on its benefits, limitation, and challenges, and also three systematic stages, the review study was performed. The result of study was portrayed in this paper. It is regarding investigation result of hybrid cryptography (HC, as one of defense methods) realized for WSN to methodically increase the security level and decrease the resources usage. The result concluded that HC was proven in escalating the security defense level and downgrading the resources use on WSN compared to symmetric and asymmetric algorithms.

关键词： Wireless sensor networks Cryptography Libraries Protocols Systematics Bibliographies

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