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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Qicong Xie Xiaohai Tian Guanghou Liu Kun Song Lei Xie Zhiyong Wu Hai Li Song Shi Haizhou Li Fen Hong Hui Bu Xin Xu ASLP@NPU School of Computer Science Northwestern Polytechnical University China National University of Singapore Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China iQIYI Inc China Machine Listening Lab University of Bremen Germany Originbeat Inc China Beijing Shell Shell Technology Co. Ltd China

The Multi-speaker Multi-style Voice Cloning Challenge (M2VoC) aims to provide a common sizable dataset as well as a fair testbed for the benchmarking of the popular voice cloning task. Specifically, we formulate the challenge to adapt an average TTS model to the stylistic target voice with limited data from target speaker, evaluated by speaker identity and style similarity. The challenge consists of two tracks, namely few-shot track and one-shot track, where the participants are required to clone multiple target voices with 100 and 5 samples respectively. There are also two sub-tracks in each track. For sub-track a, to fairly compare different strategies, the participants are allowed to use only the training data provided by the organizer strictly. For sub-track b, the participants are allowed to use any data publicly available. In this paper, we present a detailed explanation on the tasks and data used in the challenge, followed by a summary of submitted systems and evaluation results.

关键词： Deep learning Target tracking Conferences Cloning Training data Signal processing Data models

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Analysis of the association between image resolution and landscape metrics using multi-sensor LULC maps

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Planning Outlook Series 1 2024年第10期67卷

作者： Beril Varol Szilard Szabo Raziye Hale Topaloğlu Gül Aslı Aksu Elif Sertel a Graduate Program of Geomatics Engineering Istanbul Technical University Graduate School of Science Engineering and Technology Istanbul Turkiye b Department of Physical Geography and Geoinformatics Faculty of Science and Technology University of Debrecen Debrecen Hungary c Faculty of Civil Engineering Department of Geomatics Yildiz Technical University Istanbul Turkiye d Faculty of Engineering and Architecture Department of Landscape Architecture Kastamonu University Kastamonu Turkiye e Faculty of Civil Engineering Department of Geomatics Engineering Istanbul Technical University Istanbul Turkiye

This study aims to investigate the changes in landscape metrics with varying spatial resolution from Sentinel-2 (10 m), SPOT 7 (1.5 m), Pleaides (0.5 m), and Worldview-4 (0.3 m) images. We implemented Geographic Object-Based Image Analysis (GEOBIA) techniques to all images to identify 21 land use and land cover (LULC) classes, which were then used to calculate several landscape metrics. We performed the Welch hypothesis testing on the class-level landscape metrics and applied Standardized Principal Component Analysis (PCA) with the correlation matrix to reveal the multivariate pattern of landscape metrics. Our results showed that 10 m and even the 1.5 m spatial resolutions cannot guarantee the identification of all LULC classes, and class areas change with varying spatial resolution (sometimes with 200% differences). Sentinel-2 images have some limitations, specifically from the landscape ecological planning perspective; on the other hand, Pleaides and Worldview-4 seem good alternatives to understand habitats’ viability and landscape isolation/connectivity.

关键词： GEOBIA land use/land cover (LULC) mapping landscape pattern urban habitats spatial resolution

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Emergence of a predominant sequence type ST7363 and the increasing trend of resistance to cefixime and ceftriaxone in Neisseria gonorrhoeae in Southern Taiwan, 2019-2021

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Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi 2023年第4期56卷 833-841页

作者： Hsuan-Han Lin Jia-Wen Li Tsung-Ying Yang Chun-Yuan Lee Shu-Huei Jain Shang-Yi Lin Po-Liang Lu School of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of General Medicine Department of Medical Education Shin Kong Wu Ho-Su Memorial Hospital Taiwan. Fengshan Li Jiawen Urology Clinic Kaohsiung Taiwan. Center for Liquid Biopsy and Cohort Research Kaohsiung Medical University Kaohsiung Taiwan Department of Medical Laboratory Science I-Shou University Taiwan. Division of Infectious Diseases Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Graduate Institute of Clinical Medicine Kaohsiung Medical University Kaohsiung Taiwan M.Sc. Program in Tropical Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan ROC. Division of Infectious Diseases Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan. Department of Laboratory Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan. Division of Infectious Diseases Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan School of Post-Baccalaureate Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Biological Science and Technology College of Biological Science and Technology National Yang Ming Chiao Tung University Taiwan. Electronic address: d830166@***.

BACKGROUND/PURPOSE:Multi-drug resistance and the presence of epidemic lineages of Neisseria gonorrhoeae locally and globally were important clinical and public health issues. We aimed to investigate the molecular epidemiology and the antimicrobial susceptibility profiles of N. gonorrhoeae in Southern Taiwan. METHODS:Between 2019 and 2021, adult patients who had suspected gonorrhea and attended a urology clinic in southern Taiwan were recruited to participate in this study. Clinical data from medical records and a questionnaire, antimicrobial susceptibility testing using a disk diffusion test in accordance with the guidelines by the Clinical and Laboratory Standards Institute, and Multi-locus sequence typing (MLST) were analyzed. RESULTS:A total of 500 patients participated in the surveillance study. Among them, 232 N. gonorrhoeae isolates were identified, but only 164 isolates were recovered for further research. ST7363 (n = 83, 50.61%) was found to be the predominant sequence type, followed by ST1583 (n = 24, 14.63%), ST1588 (n = 13, 7.93%), and ST7827 (n = 12, 7.32%). 100% resistance to penicillin and 99.4% non-susceptible rate of ciprofloxacin were observed. The azithromycin resistant rate being 15.24% and the cefixime non-susceptible rate being 17.07% were alarming, both with decreasing trends in susceptibilities during 2019-2021. The 25 azithromycin resistant isolates were mainly belonged to ST7363 (n = 12) and ST7827 (n = 3). Seven (4.2%) isolates were ceftriaxone non-susceptible. Among them, four were assigned to be ST 7827 and three belonged to ST7363. CONCLUSION:We observed the emergence of a predominant sequence type ST7363 in southern Taiwan. Compared with previous Taiwan studies, the increasing trend of resistance to cefixime and ceftriaxone necessitates clinicians' alertness for clinical treatment response of the extended spectrum cephalosporins and the further surveillance monitor.

关键词： Antimicrobial susceptibility Gonorrhea Molecular epidemiology

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EPITA-ADAPT at SemEval-2019 task 3: Using deep sentiment analysis models and transfer learning for emotion detection in textual conversations 13

EPITA-ADAPT at SemEval-2019 task 3: Using deep sentiment ana...

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13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019

作者： Bouchekif, Abdessalam Joshi, Praveen Bouchekif, Latifa Afli, Haithem LSE EPITA Graduate School of Computer Science France ADAPT Centre Cork Institute of Technology Cork Ireland University Abou Bekr Belkaid-Tlemcen Algeria

ISBN: (纸本)9781950737062

Messaging platforms like WhatsApp, Facebook Messenger and Twitter have gained recently much popularity owing to their ability in connecting users in real-time. The content of these textual messages can be a useful resource for text mining to discover and unhide various aspects, including emotions. In this paper we present our submission for SemEval 2019 task'EmoContext'. The task consists of classifying a given textual dialogue into one of four emotion classes: Angry, Happy, Sad and Others. Our proposed system is based on the combination of different deep neural networks techniques. In particular, we use Recurrent Neural Networks (LSTM, B-LSTM, GRU, B-GRU), Convolutional Neural Network (CNN) and Transfer Learning (TL) methods. Our final system, achieves an F1µ score of 74.51% on the subtask evaluation dataset. © 2019 Association for Computational Linguistics

关键词： Sentiment analysis

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Deep learning-based identification of steel products 14th

Deep learning-based identification of steel products

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14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018

作者： Kang, Li-Wei Chen, You-Ting Jhong, Wei-Chen Hsu, Chao-Yung Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Artificial Intelligence Recognition Industry Service Research Center National Yunlin University of Science and Technology Yunlin Taiwan Automation and Instrumentation System Development Sec China Steel Corporation Kaohsiung Taiwan

ISBN: (纸本)9783030037475

To achieve smart manufacturing in Industry 4.0 for steel industry (or Steel 4.0), this paper proposes a smart steel manufacturing framework, where a deep learning-based automatic identification tracking method for steel products is developed. Automatically online tracking and identifying steel products on a production line is essential for smart manufacturing management since those products might be frequently moved and processed everywhere on the product flow. Existing approaches usually rely upon marking or embedding a series of identification codes on the steel surfaces. However, steel-making is usually processed under a very high temperature environment, making it difficult to well embed the identification codes with acceptable quality for further automatically online recognizing them. To tackle this problem, this paper presents a vision-based automatic identification tracking method without needing to embed any identification codes onto the steel product surfaces. The key idea is to utilize the essential identity of a steel product without extrinsic information embedded, achieved by automatically and deeply learning visual features from the steel image. The presented preliminary results have verified the efficiency of the proposed method. © Springer Nature Switzerland AG 2019.

关键词： Neural networks

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Complexity of computing the anti-ramsey numbers for paths 45

Complexity of computing the anti-ramsey numbers for paths

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45th International Symposium on Mathematical Foundations of computer science, MFCS 2020

作者： Amiri, Saeed Akhoondian Popa, Alexandru Roghani, Mohammad Shahkarami, Golnoosh Soltani, Reza Vahidi, Hossein University of Cologne Germany University of Bucharest Romania National Institute of Research and Development in Informatics Bucharest Romania Max Planck Institute for Informatics Saarland Informatics Campus Saarbrücken Germany Sharif University of Technology Teheran Iran MPI for Informatics Saarland Informatics Campus Graduate School of Computer Science Saarbrücken Germany

ISBN: (纸本)9783959771597

The anti-Ramsey numbers are a fundamental notion in graph theory, introduced in 1978, by Erdös, Simonovits and Sós. For given graphs G and H the anti-Ramsey number ar(G, H) is defined to be the maximum number k such that there exists an assignment of k colors to the edges of G in which every copy of H in G has at least two edges with the same color. Usually, combinatorists study extremal values of anti-Ramsey numbers for various classes of graphs. There are works on the computational complexity of the problem when H is a star. Along this line of research, we study the complexity of computing the anti-Ramsey number ar(G, Pk), where Pk is a path of length k. First, we observe that when k is close to n, the problem is hard;hence, the challenging part is the computational complexity of the problem when k is a fixed constant. We provide a characterization of the problem for paths of constant length. Our first main contribution is to prove that computing ar(G, Pk) for every integer k > 2 is NP-hard. We obtain this by providing several structural properties of such coloring in graphs. We investigate further and show that approximating ar(G, P3) to a factor of n−1/2−Ε is hard already in 3-partite graphs, unless P = NP. We also study the exact complexity of the precolored version and show that there is no subexponential algorithm for the problem unless ETH fails for any fixed constant k. Given the hardness of approximation and parametrization of the problem, it is natural to study the problem on restricted graph families. Along this line, we first introduce the notion of color connected coloring, and, employing this structural property, we obtain a linear time algorithm to compute ar(G, Pk), for every integer k, when the host graph, G, is a tree. © Nathalie Bertrand;licensed under Creative Commons License CC-BY 45th International Symposium on Mathematical Foundations of computer science (MFCS 2020).

关键词： Color

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Ammonia: An approach for deriving project-specific bug patterns

arXiv

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arXiv 2020年

作者： Higo, Yoshiki Hayashi, Shinpei Hata, Hideaki Nagappan, Meiyappan Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Suita Osaka565-0871 Japan School of Computing Tokyo Institute of Technology Ookayama 2-12-1-W8-71 Ookayama Meguro-ku Tokyo152-8550 Japan Graduate School of Science and Technology Nara Institute of Science and Technology 8916-5 Takayama-cho Ikoma Nara630-0192 Japan Cheriton School of Computer Science University of Waterloo 200 University Avenue West WaterlooON Canada

Finding and fixing buggy code is an important and cost-intensive maintenance task, and static analysis (SA) is one of the methods developers use to perform it. SA tools warn developers about potential bugs by scanning their source code for commonly occurring bug patterns, thus giving those developers opportunities to fix the warnings (potential bugs) before they release the software. Typically, SA tools scan for general bug patterns that are common to any software project (such as null pointer dereference), and not for project specific patterns. However, past research has pointed to this lack of customizability as a severe limiting issue in SA. Accordingly, in this paper, we propose an approach called Ammonia, which is based on statically analyzing changes across the development history of a project, as a means to identify project-specific bug patterns. Furthermore, the bug patterns identified by our tool do not relate to just one developer or one specific commit, they reflect the project as a whole and compliment the warnings from other SA tools that identify general bug patterns. Herein, we report on the application of our implemented tool and approach to four Java projects: Ant, Camel, POI, and Wicket. The results obtained show that our tool could detect 19 project specific bug patterns across those four projects. Next, through manual analysis, we determined that six of those change patterns were actual bugs and submitted pull requests based on those bug patterns. As a result, five of the pull requests were merged. Copyright © 2020, The Authors. All rights reserved.

关键词： Static analysis

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DESHIMA 2.0: Rapid redshift surveys and multi-line spectroscopy of dusty galaxies

arXiv

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arXiv 2021年

作者： Rybak, Matus Bakx, T. Baselmans, J. Karatsu, K. Kohno, K. Takekoshi, T. Tamura, Y. Taniguchi, A. van der Werf, P. Endo, A. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Leiden Observatory Leiden University Niels Bohrweg 2 Leiden2333 CA Netherlands Division of Particle and Astrophysical Science Graduate School of Science Nagoya University Furocho Chikusa-ku Aichi Nagoya464-8602 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Tokyo Mitaka181-8588 Japan SRON Netherlands Institute for Space Research Niels Bohrweg 4 Leiden2333 CA Netherlands Institute of Astronomy Graduate School of Science The University of Tokyo 2-21-1 Osawa Tokyo Mitaka181-0015 Japan Research Center for the Early Universe Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan

We present a feasibility study for the high-redshift galaxy part of the science Verification Campaign with the 220-440 GHz DESHIMA 2.0 integrated superconducting spectrometer on the ASTE telescope. The first version of the DESHIMA 2.0 chip has been recently manufactured and tested in the lab. Based on these realistic performance measurements, we evaluate potential target samples and prospects for detecting the [CII] and CO emission lines. The planned observations comprise two distinct, but complementary objectives: (1) acquiring spectroscopic redshifts for dusty galaxies selected in far-infrared/mm-wave continuum surveys;(2) multi-line observations to infer physical conditions in dusty galaxies. © 2021, CC BY.

关键词： Galaxies

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An ICN system focusing on distributed MQTT Brokers for IoT services 7

An ICN system focusing on distributed MQTT Brokers for IoT s...

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7th International Japan-Africa Conference on Electronics, Communications and Computations, JAC-ECC 2019

作者： Terada, Keitaro Ohno, Shuichi Mukai, Hiroaki Ishibashi, Koichi Yokotani, Tetsuya Graduate School of Information and Computer Science Kanazawa Institute of Technology Hakusan Ishikawa Japan College of Engineering Kanazawa Institute of Technology Department of Electrical and Electronics Engineering Nonoichi Ishikawa Japan

ISBN: (数字)9781728156170

ISBN: (纸本)9781728156170

Network technologies for the Internet of Things (IoT) have been widely discussed for real time deployment. In the IoT services, a huge number of small packets are transferred across the networks. If the current Internet technologies are applied to these services, a large overhead is caused by the IP routing process, information discovery, and large protocol headers, such as HTTP over TCP. In addressing this problem, the application of Information Centric Network (ICN) technologies to the IoT services holds promise. However, this has a disadvantage in that a network based on the ICN technologies is expanded to a larger area. This study proposes a solution to this problem through a framework of a distributed ICN system for the IoT services. In the proposed approach, the end points are invoked by the ICN related protocols. Interworking points are invoked to connect among themselves by a logical loop and cached information is transferred in real time through 'shared memory architecture'. This study also presents the detailed operations based on this approach. © 2019 IEEE.

关键词： Internet of things

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Promotion of the Catalytic Polymerization of Hydroquinone Towards Humic-Like Substances by Graphitic Carbon Nitride

SSRN

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SSRN 2023年

作者： Ahmed, Mahmoud M.M. Liu, Yu-Ting Venkatesan, Srinivasadesikan Wu, Min Chien Nail, Howida M. Tzou, Der-Lii M. Lin, Ming-Chang Chen, Kai-Yue Tzou, Yu-Min Department of Soil and Environmental Sciences National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Innovation and Development Center of Sustainable Agriculture National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Department of Chemistry School of Science and Humanities Vignan's Foundation for Science Technology and Research Guntur Andhra Pradesh Vadlamudi522 213 India Graduate institute of Biomedical Engineering National Chung Hsing University 145 Xingda Rd. Taichung40227 Taiwan Institute of Chemistry Academia Sinica Nangang Taipei11529 Taiwan Department of Applied Chemistry National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Professional Bachelor Program of Farm Management National Chiayi University Chiayi600355 Taiwan

The utilization of graphitic carbon nitride (C3N4) to enhance the oxidative polymerization of hydroquinone (HQ) within birnessite (δ-MnO2) systems was investigated. C3N4, a Lewis base enriched with nitrogen, acted as a bridge through π−π interactions between metal oxides and polyphenols. These interactions increased the affinity of the reactants, resulting in an enhanced reaction rate of six-fold, accelerated browning, and improved complex stability of C3N4...HQ...MnO2 complex. As a result, a humic-like substance (HS) was rapidly formed with improved surface morphology and larger particle sizes. Electron transfer of HQ...MnO2 promoted by C3N4 played a crucial role in HQ oxidation, expanding atomic distance and composite morphology. Theoretical calculations supported the experimental results, indicating strong affinity and higher binding energies in the C3N4...HQ...MnO2 complex. The complex had a more stable structure with a narrower HOMO-LUMO gap, facilitating HS formation. 13C and 1H NMR spectra confirmed the experimental-theoretical agreement. © 2023, The Authors. All rights reserved.

关键词： Binding energy

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