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32nd European Safety and Reliability Conference, ESREL 2022

作者： Kammouh, Omar Marandi, Ahmadreza Fecarotti, Claudia Department of Multi-Actor Systems Faculty of Technology Policy and Management Delft University of Technology Netherlands Department of Industrial Engineering and Innovation Sciences Eindhoven University of Technology Netherlands

ISBN: (纸本)9789811851834

The well-being of modern societies depends on the functioning of their infrastructure networks. During their service lives, infrastructure networks are subject to different stresses (e.g., deterioration, hazards, etc.). Interventions are performed to ensure the continuous fulfillment of the infrastructure's functional goals. To guarantee a high level of infrastructure availability and serviceability with minimal intervention costs, preventive intervention planning is essential. Finding the optimal grouping strategy of intervention activities is an NP-hard problem that is well studied in the literature and for which various economic models and optimization approaches are proposed. This research focuses on a new efficient optimization model to cope with the intervention grouping problem of interconnected multicomponent systems. We propose a scalable two-step intervention grouping model based on a clustering technique. The clustering technique is formulated using Integer Linear programing, which guarantees the convergence to global optimal solutions of the considered problem. The proposed optimization model can account for the interactions between multiple infrastructure networks and the impact on multiple stakeholders (e.g., society and infrastructure operators). The model can also accommodate different types of intervention, such as maintenance, removal, and upgrading. We show the performance of the proposed model using a demonstrative example. Results reveal a substantial reduction in net costs. In addition, the optimal intervention plan obtained in the analysis shows repetitive patterns, which indicates that a rolling horizon strategy could be adopted so that the analysis is only performed for a short time horizon. © 2022 ESREL2022 Organizers. Published by Research Publishing, Singapore.

关键词： Integer programming

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Cofilin-Mediated Filament Softening and Crosslinking Counterbalance to Enhance Actin Network Flexibility

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Physical Review Letters 2024年第21期133卷 218402-218402页

作者： Zachary Gao Sun Michael Murrell Department of Physics Yale University 217 Prospect Street New Haven Connecticut 06511 USA Systems Biology Institute Yale University West Haven Connecticut 06516 USA Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Biomedical Engineering Yale University New Haven Connecticut 06511 USA

Filamentous-actin (F-actin) crosslinking within the cell cytoskeleton mediates the transmission of mechanical forces, enabling changes in cell shape, as occurs during cell division and cell migration. Crosslinking by actin binding proteins (ABPs) generally increases the connectivity of the F-actin network, but also increases network rigidity. As a result, there is a narrow range in the concentration of crosslinker protein at which F-actin networks are both connected and labile. Another ABP, cofilin, severs F-actin filaments at high pH through increasing their bending flexibility and concentrating mechanical stress, inducing fragmentation. By contrast, at lower pH, cofilin increases filament flexibility yet does not sever. Instead, it forms disulfide bonds, which crosslink F-actin into bundles, and bundles into networks. Here, we combine light microscopy and rheology to determine the impact of two potentially opposing effects on the mechanics of F-actin networks—increased flexibility at the filament level, and increased connectivity at the network level. Indeed, by linear rheology, we find that these mechanisms are counterbalanced, such that cofilactin network moduli are only weakly dependent on cofilin concentration over a broad range, in contrast to the dramatic stiffening that occurs with F-actin crosslinking protein. Further, by nonlinear rheology, the network stiffens at a higher stress than crosslinking protein, indicative of a broader range in which the material remains flexible. These results may enable F-actin networks to increase connectivity without heavy penalties to rigidity, and thus provide a new route to modulating active polymer mechanics unseen using traditional F-actin accessory proteins.

关键词： Biomimetic & bio-inspired materials Biomolecular self-assembly Living matter & active matter Persistence length Polymer entanglement Rheological properties Rheology Shear deformation Strain

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Toward a Patient-Centered Care Supporting System: Integration of Multidisciplinary Health Records in Breast Cancer Care

Toward a Patient-Centered Care Supporting System: Integratio...

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34th Medical Informatics Europe Conference, MIE 2024

作者： Sugiyama, Atsuko Utsunomiya, Kazuki Okumiya, Hayato Fujimoto, Katsuhiko Shimomura, Yuka Sanuki, Masaru Kume, Keitaro Yano, Takahiro Kagawa, Rina Bando, Hiroko Canon Medical Systems Corporation Tochigi Otawara Japan Graduate School of Biomedical Engineering Tohoku University Miyagi Sendai Japan Laboratory of Mathematical Informatics in Medicine University of Tsukuba Ibaraki Tsukuba Japan Department of Biomedical Informatics and Management University of Tsukuba Hospital Ibaraki Tsukuba Japan Department of Breast-Thyroid-Endocrine Surgery Institute of Medicine University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9781643685335

An important paradigm shift within healthcare is the shift toward patient-centered care (PCC). Multidisciplinary team meetings (MDTM) are considered essential for PCC, despite being considered time-consuming and expensive. Patient-centered information (PCI) is known to improve the quality of care. This study investigated where and how the PCI of multidisciplinary professionals' health records exists, and to explore the possibility of a sustainable PCC-supporting healthcare system. We performed an exploratory pilot study of the patient records of three patients with breast cancer. We observed that PCI was documented throughout the care pathway in the cases examined. However, we also found that these data were fragmented and scattered across various medical records, and they were also from different point of views and patient care perspectives. PCI was founded to be less accessible than traditional medical records and was even hard to find using a manual search. We therefore propose that preparing PCI for MDTM may be one of the obvious burdens for healthcare professionals (HPs). We do however believe that integrating PCI from multiple professionals' records likely plays an important function in a shift towards PCC and serves to improve not only the quality of care but also the HPs' experiences without additional burden and could contribute to a more sustainable health care system. © 2024 The Authors.

关键词： Electronic health record

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Guest editorial: Latin American perspectives on sustainability in higher education

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International Journal of Sustainability in Higher Education 2023年第2期24卷 233-234页

作者： Izabela Simon Rampasso Rosley Anholon Osvaldo Luiz Gonçalves Quelhas Luis Velazquez Claudia Mac-Lean Departamento de Ingeniería Industrial Universidad Católica del Norte Antofagasta Chile School of Mechanical Engineering State University of Campinas Campinas Brazil Master Program in Management Systems and Doctoral Program in Sustainable Management Systems Federal Fluminense University Niterói Brazil Department of Industrial Engineering Division of Engineering University of Sonora Hermosillo Mexico GAIA Antarctic Research Center Universidad de Magallanes Punta Arenas Chile

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A Fusion of Residual Blocks and Stack Auto Encoder Features for Stomach Cancer Classification

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Computers, Materials & Continua 2023年第12期77卷 3895-3920页

作者： Abdul Haseeb Muhammad Attique Khan Majed Alhaisoni Ghadah Aldehim Leila Jamel Usman Tariq Taerang Kim Jae-Hyuk Cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut1100Lebanon College of Computer Science and Engineering University of Ha’ilHa’il81451Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428RiyadhSaudi Arabia Department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Diagnosing gastrointestinal cancer by classical means is a hazardous *** have witnessed several computerized solutions for stomach disease detection and ***,the existing techniques faced challenges,such as irrelevant feature extraction,high similarity among different disease symptoms,and the least-important features from a single *** paper designed a new deep learning-based architecture based on the fusion of two models,Residual blocks and Auto ***,the Hyper-Kvasir dataset was employed to evaluate the proposed *** research selected a pre-trained convolutional neural network(CNN)model and improved it with several residual *** process aims to improve the learning capability of deep models and lessen the number of ***,this article designed an Auto-Encoder-based network consisting of five convolutional layers in the encoder stage and five in the decoder *** research selected the global average pooling and convolutional layers for the feature extraction optimized by a hybrid Marine Predator optimization and Slime Mould optimization *** features of both models are fused using a novel fusion technique that is later classified using the Artificial Neural Network *** experiment worked on the HyperKvasir dataset,which consists of 23 stomach-infected *** last,the proposed method obtained an improved accuracy of 93.90%on this *** is also conducted with some recent techniques and shows that the proposed method’s accuracy is improved.

关键词： Gastrointestinal cancer contrast enhancement deep learning information fusion feature selection machine learning

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Exploring the Effectiveness of Work from Home: A Text Mining Analysis of Employee Perceptions and Experiences

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Procedia Computer Science 2024年 234卷 448-454页

作者： Reny Nadlifatin Satria Fadil Persada Amanda Beatrice Nadya Permata Putri Michael Nayat Young Yogi Tri Prasetyo Anak Agung Ngurah Perwira Redi Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta 11480 Indonesia Industrial Engineering Department Universitas Pembangunan Nasional "Veteran" Jawa Timur Surabaya 60294 Indonesia School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila 1102 Philippines Industrial Engineering Department Faculty of Engineering and Technology Sampoerna University Jakarta 12780 Indonesia

Work from home (WFH) has become a global phenomenon that continues to grow, especially since the COVID-19 pandemic hit the world. Many organizations and companies are forced to adopt a remote working model to keep their employees safe. The usefulness of WFH is still up for dispute, though. Text mining analysis can be utilized to determine how beneficial working from home is. Sentiment analysis uses text analysis to gather ten thousand data from social media Tweets. Joy emotion is predicted to dominate with 83.98 percent according to the mining performed by the vocabulary valence aware dictionary and sentiment reasoner (VADER).

关键词： Sentiment Text mining Twitter Work from home

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SnakeGAN: A Universal Vocoder Leveraging DDSP Prior Knowledge and Periodic Inductive Bias

SnakeGAN: A Universal Vocoder Leveraging DDSP Prior Knowledg...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Sipan Li Songxiang Liu Luwen Zhang Xiang Li Yanyao Bian Chao Weng Zhiyong Wu Helen Meng Shenzhen International Graduate School Tsinghua University Shenzhen China AI Lab Tencent Inc Shenzhen China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong China

Generative adversarial network (GAN)-based neural vocoders have been widely used in audio synthesis tasks due to their high generation quality, efficient inference, and small computation footprint. However, it is still challenging to train a universal vocoder which can generalize well to out-of-domain (OOD) scenarios, such as unseen speaking styles, non-speech vocalization, singing, and musical pieces. In this work, we propose SnakeGAN, a GAN-based universal vocoder, which can synthesize high-fidelity audio in various OOD scenarios. SnakeGAN takes a coarse-grained signal generated by a differentiable digital signal processing (DDSP) model as prior knowledge, aiming at recovering high-fidelity waveform from a Mel-spectrogram. We introduce periodic nonlinearities through the Snake activation function and anti-aliased representation into the generator, which further brings desired inductive bias for audio synthesis and significantly improves the extrapolation capacity for universal vocoding in unseen scenarios. To validate the effectiveness of our proposed method, we train SnakeGAN with only speech data and evaluate its performance for various OOD distributions with both subjective and objective metrics. Experimental results show that SnakeGAN significantly outperforms the compared approaches and can generate high-fidelity audio samples including unseen speakers with unseen styles, singing voices, instrumental pieces, and nonverbal vocalization.

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach

Minimizing the Number of Stunting Prevalence Using the Eucli...

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International Conference of Computer Science and Information Technology

作者： Muhammad Zarlis Tanty Oktavia Relita Buaton Ferda Ernawan Kevin Andrian Department BINUS Graduate Program - Master of Information System Management Information System Management Bina Nusantara University Jakarta Indonesia Informatics Engineering STMIK Kaputama Binjai Indonesia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.

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HAPS-Enabled V2X Architecture for Hyper Reliable and Low-Latency Communication (HRLLC) in 6G Networks

HAPS-Enabled V2X Architecture for Hyper Reliable and Low-Lat...

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International Conference on Communications, Signal Processing, and their Applications (ICCSPA)

作者： Ahmet Melih Ince Ayse Elif Canbilen Halim Yanikomeroglu Graduate Education Institute Konya Technical University Konya Turkey Department of Systems and Computer Engineering Carleton University Ottawa Canada Department of Electrical and Electronics Engineering Konya Technical University Konya Turkey

ISBN: (数字)9798350384819

ISBN: (纸本)9798350384826

The inherent disadvantages of terrestrial environments make it difficult to meet the requirements of emerging technologies. The increasing demand for ubiquitous connectivity, which is essential for sixth generation (6G) wireless communications, requires the investigation of non-terrestrial networks (NTN) to overcome the limitations of terrestrial environments. Among NTN, high altitude platform stations (HAPS) stand out as a pivotal enabler, offering significant advantages in terms of platform size, load capacity, line-of-sight (LOS) availability, sustainability and power and energy efficiency. Envisioning the International Mobile Telecommunications (IMT) for 2030 and beyond (IMT-2030), this study focuses on the integration of HAPS into vehicle-to-everything (V2X) technology, particularly in the context of autonomous vehicle networks, to facilitate hyper reliable and low-latency communication (HRLLC). The role of HAPS in enhancing data processing and communication efficiency for V2X is critically analyzed, highlighting their contribution to vehicle positioning, environmental sensing, and decision-making processes-core components for the safe realization of V2X. Specifically, a prospective scenario for achieving HRLLC by integrating HAPS into V2X is presented, and the contributions of HAPS on managing the extensive data traffic and real-time processing challenges in V2X is discussed by proposing an artificial intelligence based solution. The discussion is extended to the challenges of handling the vast volumes of data generated, emphasizing the need for efficient data traffic classification and traffic management strategies. In conclusion, the paper highlights the remarkable potential of HAPS-enabled V2X architecture in 6G networks, articulating its significant impact on improving road safety, transportation systems, and communication efficiency. It seems that a more interconnected and intelligent future for V2X technology providing HRLLC is on the horizon.

关键词： 6G mobile communication Decision making Transportation Data processing Telecommunication network reliability Data communication Low latency communication Artificial intelligence Vehicle-to-everything Autonomous vehicles

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STYLESPEECH: SELF-SUPERVISED STYLE ENHANCING WITH VQ-VAE-BASED PRE-TRAINING FOR EXPRESSIVE AUDIOBOOK SPEECH SYNTHESIS

arXiv

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arXiv 2023年

作者： Chen, Xueyuan Wang, Xi Zhang, Shaofei He, Lei Wu, Zhiyong Wu, Xixin Meng, Helen Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Shenzhen International Graduate School Tsinghua University Shenzhen China Microsoft Beijing China

The expressive quality of synthesized speech for audiobooks is limited by generalized model architecture and unbalanced style distribution in the training data. To address these issues, in this paper, we propose a self-supervised style enhancing method with VQ-VAE-based pre-training for expressive audiobook speech synthesis. Firstly, a text style encoder is pre-trained with a large amount of unlabeled text-only data. Secondly, a spectrogram style extractor based on VQ-VAE is pre-trained in a self-supervised manner, with plenty of audio data that covers complex style variations. Then a novel architecture with two encoder-decoder paths is specially designed to model the pronunciation and high-level style expressiveness respectively, with the guidance of the style extractor. Both objective and subjective evaluations demonstrate that our proposed method can effectively improve the naturalness and expressiveness of the synthesized speech in audiobook synthesis especially for the role and out-of-domain scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Speech synthesis

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