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Investigation of manufacturing conditions of single roll rapidly solidified ribbon for anode materials of magnesium rechargeable batteries

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Keikinzoku/Journal of Japan Institute of Light Metals 2023年第11期73卷 537-544页

作者： Kirimoto, Yuichi Fuke, Kousuke Tsukeda, Tadayoshi Aida, Tetsuo Nemoto, Yasunori Ikeda, Minoru Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Department of Nano and Functional Material Science Graduate School of Science and Engineering for Education University of Toyama 3190 Gofuku Toyama-shi-shiToyama Toyama930-8555 Japan Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama Toyama-shi-shiToyama Toyama Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama-shi-shiToyama Toyama Japan FLOW Science JAPAN Shizuoka Hamamatsu-shi Japan CHUETSU METAL WORKS CO. LTD Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Saitama Kawaguchi-shi Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

Magnesium rechargeable batteries are attracting attention as next-generation rechargeable batteries because of their resource abundance, cost, safety, and high electrical capacity per volume compared to conventional lithium-ion rechargeable batteries. Our joint research team focused not only on the electrochemically active magnesium composition of ribbon for the negative electrode materials of magnesium rechargeable batteries but also on the production process, focused on the single roll type liquid quenching and rapid solidification method, which can be produced at a lower cost. In this study, the optimal processing conditions were examined by comparing CAE analysis with ribbon actually manufactured, with the aim of further improving manufacturing conditions using the same method, such as length discontinuities, thickness, and surface properties of ribbon. We specifically various process parameters such as injection pressure and roll peripheral speed for evaluation. As a result, several linear cracks were observed on the surface of the ribbon as the peripheral speed increased and as the Gap became wider, and the surface properties tended to deteriorate. Also, It was found that the dominant factor in the length of the ribbon was the peripheral speed. As the peripheral speed increased, the length of the ribbon tended to increase. © 2023 Japan Institute of Light Metals. All rights reserved.

关键词： Surface properties

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Inter-radar Interference Mitigation via Self-attention Augmented biGRU and Customized Loss Functions

Inter-radar Interference Mitigation via Self-attention Augme...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Yudai Suzuki Xiaoyan Wang Masahiro Umehira Hao Zhou Graduate School of Science and Engineering Ibaraki University Hitachi Japan Department of Electronics and Communication Technology Nanzan University Nagoya Japan School of Computer Science University of Science and Technology of China Hefei China

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

CS (Chirp Sequence) radars are one of the most essential sensors for perceiving the surrounding environment in automotive applications. However, as the number of radar sensors increases, inter-radar interference becomes more prevalent, leading to a severe degradation in target detection rates. To address this issue, we propose a self-attention augmented dual-channel biGRU model to mitigate wideband interference, and explore various customized loss functions to enhance its performance. Specifically, the dual-channel biGRU processes the real and imaginary components of the radar beat signal simultaneously, while multi-head self-attention enhances the model’s focus on critical segments of the input signal. Additionally, the customized loss functions either incorporate both time and frequency domain information or utilize both interfered and interference-free samples to more effectively reconstruct the beat signal. The effectiveness of the proposed interference mitigation method is validated through extensive simulations, showing superior performance in terms of SNR (Signal-to-Noise Ratio), amplitude absolute error, phase absolute error, and F1 score compared to existing approaches.

关键词： Prevention and mitigation Radar detection Interference Radar Object detection Radar imaging Radar signal processing Sensors Wideband Signal to noise ratio

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E-Learning Satisfaction: Analysis of the Support Factors 10

E-Learning Satisfaction: Analysis of the Support Factors

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10th International Conference on Information technology, computer, and Electrical Engineering, ICITACEE 2023

作者： Siswanto, Boby Alamsyah, Doni Purnama Morika, Doni Othman, Norfaridatul Akmaliah Wijaya, Billiam Christofer Adinda, Putri Giyan Bina Nusantara University Computer Science Study Program School of Computer Science Jakarta11480 Indonesia Bina Nusantara University BINUS Business School Entrepreneurship Department Jakarta11480 Indonesia Bina Nusantara University Interior Design Study Program School of Design Jakarta11480 Indonesia Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka76100 Malaysia

ISBN: (纸本)9798350322729

E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e-learning platform, using Big Data technology as the basis for its development. © 2023 IEEE.

关键词： E-learning

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STREAMING PIANO TRANSCRIPTION BASED ON CONSISTENT ONSET AND OFFSET DECODING WITH SUSTAIN PEDAL DETECTION

arXiv

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arXiv 2025年

作者： Wei, Weixing Zhao, Jiahao Wu, Yulun Yoshii, Kazuyoshi Graduate School of Informatics Kyoto University Japan School of Computer Science and Technology Fudan University China Graduate School of Engineering Kyoto University Japan

This paper describes a streaming audio-to-MIDI transcription method that can sequentially translate a piano recording into a sequence of note-on and note-off events. The sequence-to-sequence learning nature of this task may call for using a Transformer model, which has been used for offline transcription and could be extended for streaming transcription with a causal restriction of the attention mechanism. We assume that the decoder of this model suffers from the performance limitation. Although time-frequency features useful for onset detection are considerably different from those for offset detection, the single decoder is trained to output a mixed sequence of onset and offset events without guarantee of the correspondence between the onset and offset events of the same note. To overcome this limitation, we propose a streaming encoder-decoder model that uses a convolutional encoder aggregating local acoustic features, followed by an autoregressive transformer decoder detecting a variable number of onset events and another decoder detecting the offset events of the active pitches with validation of the sustain pedal at each time frame. Experiments using the MAESTRO dataset showed that the proposed streaming method performed comparably with or even better than the state-of-the-art offline methods while significantly reducing the computational cost. Copyright © 2025, The Authors. All rights reserved.

关键词： Decoding

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SpeechCraft: A Fine-Grained Expressive Speech Dataset with Natural Language Description 24

SpeechCraft: A Fine-Grained Expressive Speech Dataset with N...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Jin, Zeyu Jia, Jia Wang, Qixin Li, Kehan Zhou, Shuoyi Zhou, Songtao Qin, Xiaoyu Wu, Zhiyong Department of Computer Science and Technology Tsinghua University Beijing China BNRist Tsinghua University Key Laboratory of Pervasive Computing Ministry of Education Beijing China Shenzhen International Graduate School Tsinghua University Shenzhen China

ISBN: (纸本)9798400706868

Speech-language multi-modal learning presents a significant challenge due to the fine nuanced information inherent in speech styles. Therefore, a large-scale dataset providing elaborate comprehension of speech style is urgently needed to facilitate insightful interplay between speech audio and natural language. However, constructing such datasets presents a major trade-off between large-scale data collection and high-quality annotation. To tackle this challenge, we propose an automatic speech annotation system for expressiveness interpretation that annotates in-the-wild speech clips with expressive and vivid human language descriptions. Initially, speech audios are processed by a series of expert classifiers and captioning models to capture diverse speech characteristics, followed by a fine-tuned LlaMA for customized annotation generation. Unlike previous tag/templet-based annotation frameworks with limited information and diversity, our system provides in-depth understandings of speech style through tailored natural language descriptions, thereby enabling accurate and voluminous data generation for large model training. With this system, we create SpeechCraft, a fine-grained bilingual expressive speech dataset. It is distinguished by highly descriptive natural language style prompts, containing approximately 2,000 hours of audio data and encompassing over two million speech clips. Extensive experiments demonstrate that the proposed dataset significantly boosts speech-language task performance in stylist speech synthesis and speech style understanding. © 2024 Owner/Author.

关键词： Large datasets

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VoxInstruct: Expressive Human Instruction-to-Speech Generation with Unified Multilingual Codec Language Modelling 24

VoxInstruct: Expressive Human Instruction-to-Speech Generati...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhou, Yixuan Qin, Xiaoyu Jin, Zeyu Zhou, Shuoyi Lei, Shun Zhou, Songtao Wu, Zhiyong Jia, Jia Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China BNRist Tsinghua University Key Laboratory of Pervasive Computing Ministry of Education Beijing China

ISBN: (纸本)9798400706868

Recent AIGC systems possess the capability to generate digital multimedia content based on human language instructions, such as text, image and video. However, when it comes to speech, existing methods related to human instruction-to-speech generation exhibit two limitations. Firstly, they require the division of inputs into content prompt (transcript) and description prompt (style and speaker), instead of directly supporting human instruction. This division is less natural in form and does not align with other AIGC models. Secondly, the practice of utilizing an independent description prompt to model speech style, without considering the transcript content, restricts the ability to control speech at a fine-grained level. To address these limitations, we propose VoxInstruct, a novel unified multilingual codec language modeling framework that extends traditional text-to-speech tasks into a general human instruction-to-speech task. Our approach enhances the expressiveness of human instruction-guided speech generation and aligns the speech generation paradigm with other modalities. To enable the model to automatically extract the content of synthesized speech from raw text instructions, we introduce speech semantic tokens as an intermediate representation for instruction-to-content guidance. We also incorporate multiple Classifier-Free Guidance (CFG) strategies into our codec language model, which strengthens the generated speech following human instructions. Furthermore, our model architecture and training strategies allow for the simultaneous support of combining speech prompt and descriptive human instruction for expressive speech synthesis, which is a first-of-its-kind attempt. Codes, models and demos are at: https://***/thuhcsi/VoxInstruct. © 2024 Owner/Author.

关键词： C (programming language)

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Dagang Yuk Yuk As Smartphone Application for MSME Product Sales 2

Dagang Yuk Yuk As Smartphone Application for MSME Product Sa...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Erinda, Muhammad Fandi Warnars, Harco Leslie Hendric Spits Sumardin, Winters Arianto, Jimmy Vinarycha, Devi Wahyu Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univesity Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Many MSMEs manually close their businesses in today's competition, especially those caused by the COVID19 pandemic, and besides that, the lack of technology implementation is even more aggravating. Like it or not, Micro, Small, and Medium Enterprises (MSMEs) must equip their businesses with the application of technology, and unfortunately, there are still many MSMEs that have not been able to take advantage of the benefits of technological developments. Many companies see this condition as an opportunity;for example, Gojek and Grab partner with MSME players to make it easier to trade their products or services. In this paper, a smartphone application for MSMEs called 'Dagang Yuk Yuk, ' which consists of activities such as Login, Create Order, Input Delivery Location, Select Courier, and Select Payment Method has been proposed. Dagang Yuk Yuk tries to give different ideas for implementing MSME actors where this application is only for MSME players as part of an MSME business unit. This paper discusses the application's design using use case diagrams to describe the business process, while class diagrams model the database design. This application was developed using Arduino studio and MySQL database for database storage. © 2022 IEEE.

关键词： Competition

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Machine Learning-Based Classification of Suicidal Ideation in Tweets: A Sentiment Analysis Approach

Machine Learning-Based Classification of Suicidal Ideation i...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Orsino Jerrell Bruinier Irma Kartika Wairooy Vladimir Elwin Leonard Brilly Andro Makalew Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Mobile Application & Technology Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Suicide appears to have reached the highest public health importance, with social media like Twitter providing an infinite source of information that may help in the detection of ideation. This paper describes the development of an effective machine learning-based model for the classification of suicidal ideation in tweets using sentiment analysis. An assembly was done with a dataset of 9,120 tweets; they were labelled according to the suicidal thoughts expressed in them. We presented the assembly and preprocessing of a dataset consisting of 9,120 tweets designated based on indicative or non-indicative suicidal thoughts. The preprocessing steps consisted of normalization, tokenization, stop word removal, and lemmatization. Five ML models, namely Support Vector Machine (SVM), Multinomial Naive Bayes (MNB), Random Forest (RF), Stochastic Gradient Descent (SGD), and Logistic Regression (LR), were further trained on the selected dataset. The models are tested for standard classification metrics: accuracy, precision, recall, F1-Score, and AUC. The best performance for the model was Random Forest with 95.135% and an F1-Score of 95.094%. In conclusion, our study established that an amalgamation of sentiment analysis in ML models can have the potential to detect early suicidal tendencies and that it lays a platform for timely interventions. Future research should be focused on making the dataset even larger and enhancing the detection of sarcasm and jokes in the models.

关键词： Support vector machines Radio frequency Sentiment analysis Analytical models Accuracy Social networking (online) Blogs Training data Random forests Assembly

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ARtopia: A Mobile Application based Digital Crowdfunding Platform 2

ARtopia: A Mobile Application based Digital Crowdfunding Pla...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Daventa, Sherleen Setiawan, Andika Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Crowdfunding has become a popular term these days, and people usually do crowdfunding to raise a certain amount of money for a specific cause. There are already many popular crowdfunding portals in Indonesia where people can send support to anyone with money. When talking about crowdfunding, most people probably think of providing support to others in need, for example, those who are sick and poor. However, crowdfunding is not always like that. Crowdfunding can be applied to any field, especially in the creative industries, as the people in this report will discuss. If you do not know it beforehand, the creative industry sometimes struggles with copyright and online piracy issues. These problems will soon be very detrimental to the artists as creators. Another problem often sought is the artists themselves, especially those still amateurs. They are often hesitant to share their works and promote themselves because they do not know-how. In this case, crowdfunding application development will be necessary to facilitate all artists and content creators (such as content creators, vloggers, or even game developers) to gain support from their fans and promote themselves to become more popular. © 2022 IEEE.

关键词： Crowdsourcing

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices

Random Number Generator for Securing Data Exchange in Smart ...

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computer Technologies (ICCTech), International Conference on

作者： Andi Sama Meyliana Yaya Heryadi Taufik Roni Sahroni Computer Science Department Binus Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Information System Department School of Information System Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350395419

ISBN: (纸本)9798350395426

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information technology (IT) advancements to Operational technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption.

关键词： Industries Systematics Market research Data transfer Control systems Generators Encryption

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