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arXiv 2023年

作者： Guo, Houjian Liu, Chaoran Ishi, Carlos Toshinori Ishiguro, Hiroshi Interactive Robot Research Team Guardian Robot Project RIKEN Japan Graduate School of Engineering Science Osaka University Japan Advanced Telecommunications Research Institute International Japan

Voice conversion systems have made significant advancements in terms of naturalness and similarity in common voice conversion tasks. However, their performance in more complex tasks such as cross-lingual voice conversion and expressive voice conversion remains imperfect. In this study, we propose a novel approach that combines a jointly trained speaker encoder and content features extracted from the cross-lingual speech recognition model Whisper to achieve high-quality cross-lingual voice conversion. Additionally, we introduce a speaker consistency loss to the joint encoder, which improves the similarity between the converted speech and the reference speech. To further explore the capabilities of the joint speaker encoder, we use the Phonetic posteriorgram as the content feature, which enables the model to effectively reproduce both the speaker characteristics and the emotional aspects of the reference speech. The code and pre-trained model are open-sourced . Copyright © 2023, The Authors. All rights reserved.

关键词： Signal encoding

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Strategic Integration of HR, Organizational Management, Big Data, IoT, and AI: A Comprehensive Framework for Future-Ready Enterprises 9

Strategic Integration of HR, Organizational Management, Big ...

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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Chavan, Vaibhavi Nagendra Mohammad Roshif, U. Abhijith, R. Joshi, Amit Jha, Deepak Ravensbourne University London Project Management United Kingdom Manipal Law School Manipal Academy of Higher Education Karnataka Bengaluru India Malabar College of Advanced Studies Vengara University of Calicut Department of Management Studies Kerala India Cet School of Management College of Engineering Trivandrum Apj Abdul Kalam Technological University Kerala India Ba School of Business And Finance Riga Latvia Uttar Pradesh India

ISBN: (纸本)9798350365092

This exploration paper proposes a comprehensive frame aimed at fostering unborn-ready enterprises through the strategic integration of Human coffers(HR), Organizational Management, Big Data, the Internet of Things (IoT), and Artificial Intelligence(AI). By synthesizing these critical factors, the frame seeks to optimize organizational effectiveness, enhance decision-making processes, and acclimatize proactively to evolving request dynamics. Through a methodical review of being literature and empirical substantiation, the paper delineates the interconnectedness of these rudiments and elucidates their collaborative impact on organizational performance and dexterity. likewise, it explores perpetration strategies and implicit challenges associated with espousing such an intertwined approach. This paper not only contributes to the theoretical understanding of strategic operation but also provides practical perceptivity for directors and directors seeking to navigate the complications of the contemporary business geography and place their associations for sustained success in a decreasingly digitized and competitive terrain. © 2024 IEEE.

关键词： Data Analytics

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Rock mass joint set identification at Draa Sfar mine in Morocco through stereographic projection and K-means clustering

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Mediterranean Geoscience Reviews 2024年第1期6卷 49-56页

作者： Clero, Kaoutar Ed-Diny, Said Achalhi, Mohammed Cherkaoui, Mouhamed Benzakour, Intissar Soror, Tarik Rziki, Said El Fkihi, Sanaa Nadour, Mohamed Tagemouati, Hicham Bourzeix, François National School of Mines of Rabat (ENSMR) Hadj Ahmed Cherkaoui Avenue Agdal Rabat Morocco Moroccan Foundation for Advanced Science Innovation and Research (MASCIR) Mohamed Al Jazouli Street Madinat Al Irfane Rabat Morocco REMINEX Engineering R&D and Project Management BP 469 Marrakech Morocco National School of Computer Science and Systems Analysis (ENSIAS) IRDA Team Rabat IT Center ADMIR Lab Université Mohammed V Rabat Morocco

Rock mass joint set identification, crucial for geological and geotechnical studies, is often based on stereographic projection. However, the related software programs can eventually present some access limitations. Therefore, with the development of the Artificial Intelligence field and the sharp increase in Machine Learning and Deep Learning applications, this study aims to suggest an alternative solution for rock mass joint sets identification based on the K-means clustering algorithm, an unsupervised Machine Learning model that aims to structure unlabeled data into different clusters based on their patterns. The study includes a comparative analysis of joint set clustering using the K-means model and the stereographic projection. The two methods are applied to the structural data of the Draa Sfar deep underground mine in Morocco. The results show the concordance of the joint set clustering using both stereographic projection and the K-means model, highlighted by the mean dip and dip direction obtained values. This concordance confirms that K-means clustering allows identifying rock mass joint sets if access to stereographic projection automated tools is limited. However, using K-means clustering for this purpose requires applying preprocessing methods such as the elbow method or the silhouette score to identify the clusters' number previously. In conclusion, unsupervised learning can be an alternative for identifying rock mass joint sets as long as enough and suitable structural data are accessible. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Artificial intelligence K-means clustering Rock mass joint set Stereographic projection Structural geology Unsupervised learning

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Proposing Tap-Track Platform for Facilitating Implementation of Button-Driven Smart Services

Proposing Tap-Track Platform for Facilitating Implementation...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Ryota Murate Tomorou Nakahashi Sinan Chen Sachio Saiki Masahide Nakamura Kiyoshi Yasuda Yuta Tuyuzaki Faculty of Engineering Kobe University Kobe Japan Graduate School of Engineering Kobe University Kobe Japan School of Data and Innovation Kochi University of Technology Kochi Japan Kobe University Tokyo Japan RIKEN Center for Advanced Intelligence Project Tokyo Japan Oyumino Central Hospital Chiba Japan

ISBN: (数字)9798350366648

ISBN: (纸本)9798350366655

In recent years, the movement toward a super smart society as a future society is being promoted as Society 5.0. In this movement, smart services [1] have become very diverse, and the burden on users has increased. Therefore, in this paper, we focus on button-driven smart services, and propose a platform " Tap Track " that makes it easy to implement button-driven smart services. In Tap Track, users can create services that run when a button [2] is pressed with no code, and users can assign their desired services to the button. The processing that can be executed when the button is pressed is playing media files, sending commands to external services, and so on. The usage history of the button can be looked back later as a life log. In the case study, we created a weather forecast confirmation service and a life log service using Tap Track and verified its operation.

关键词： Seminars Codes Tracking Weather forecasting Pressing Media Registers History Graphical user interfaces

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SGLT2 inhibitor empagliflozin promotes revascularization in diabetic mouse hindlimb ischemia by inhibiting ferroptosis

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中国药理学报（英文版） 2023年第6期44卷 1161-1174页

作者： Jing-xuan Han Lai-liu Luo Yi-cheng Wang Makoto Miyagishi Vivi Kasim Shou-rong Wu Key Laboratory for Biorheological Science and Technology of Ministry of Education College of BioengineeringChongqing UniversityChongqing 400044China The 111 Project Laboratory of Biomechanics and Tissue Repair College of BioengineeringChongqing UniversityChongqing 400044China Key Laboratory for Biorheological Science and Technology of Ministry of Education College of BioengineeringChongqing UniversityChongqing 400044China The 111 Project Laboratory of Biomechanics and Tissue Repair College of BioengineeringChongqing UniversityChongqing 400044China State and Local Joint Engineering Laboratory for Vascular Implants College of BioengineeringChongqing UniversityChongqing 400044China Molecular Composite Medicine Research Group Biomedical Research InstituteNational Institute of Advanced Industrial Science and Technology(AIST)TsukubaIbaraki 305-8566Japan

Gliflozins are known as SGLT2 inhibitors,which are used to treat diabetic patients by inhibiting glucose reabsorption in kidney proximal *** studies show that gliflozins may exert other effects independent of SGLT2 *** this study we investigated their effects on skeletal muscle cell viability and paracrine function,which were crucial for promoting revascularization in diabetic hindlimb ischemia(HLI).We showed that treatment with empagliflozin(0.1-40 μM)dose-dependently increased high glucose(25 mM)-impaired viability of skeletal muscle C2C12 ***,dapagliflozin,ertugliflozin,ipragliflozin and tofogliflozin exerted similar protective effects on skeletal muscle cells cultured under the hyperglycemic *** analysis revealed an enrichment of pathways related to ferroptosis in empagliflozin-treated C2C12 *** further demonstrated that empagliflozin and other gliflozins(10 μM)restored GPX4 expression in high glucose-treated C2C12 cells,thereby suppressing ferroptosis and promoting cell ***(10 μM)also markedly enhanced the proliferation and migration of blood vessel-forming cells by promoting paracrine function of skeletal muscle C2C12 *** diabetic HLI mice,injection of empagliflozin into the gastrocnemius muscle of the left hindlimb(10mg/kg,every 3 days for 21 days)significantly enhanced revascularization and blood perfusion ***,these results reveal a novel effect of empagliflozin,a clinical hypoglycemic gliflozin drug,in inhibiting ferroptosis and enhancing skeletal muscle cell survival and paracrine function under hyperglycemic condition via restoring the expression of *** study highlights the potential of intramuscular injection of empagliflozin for treating diabetic HLI.

关键词： diabetic hindlimb ischemia empagliflozin therapeutic angiogenesis revascularization ferroptosis

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Robust tensor decomposition via orientation invariant tubal nuclear norms

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Science China(Technological Sciences) 2022年第6期65卷 1300-1317页

作者： WANG AnDong ZHAO QiBin JIN Zhong LI Chao ZHOU GuoXu School of Automation Guangdong University of TechnologyGuangzhou 510006China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Tensor Learning Team RIKEN Center for Advanced Intelligence ProjectTokyo 103-0027Japan Key Laboratory of Intelligent Perception and System for High-Dimensional Information Ministry of EducationNanjing 210094China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China

Aiming at recovering an unknown tensor(i.e.,multi-way array)corrupted by both sparse outliers and dense noises,robust tensor decomposition(RTD)serves as a powerful pre-processing tool for subsequent tasks like classification and target detection in many computer vision and machine learning ***,tubal nuclear norm(TNN)based optimization is proposed with superior performance as compared with other tensorial nuclear norms for tensor ***,one major limitation is its orientation sensitivity due to low-rankness strictly defined along tubal orientation and it cannot simultaneously model spectral low-rankness in multiple *** this end,we introduce two new tensor norms called OITNN-O and OITNN-L to exploit multi-orientational spectral low-rankness for an arbitrary K-way(K≥3)*** further formulate two RTD models via the proposed norms and develop two algorithms as the ***,we establish non-asymptotic error bounds which can predict the scaling behavior of the estimation *** on real-world datasets demonstrate the superiority and effectiveness of the proposed norms.

关键词： tensor recovery t-SVD estimation error tensor completion

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Protecting Consumer Electronics Human-Computer Interactive Verification Security via Anomaly-Aware Reconstruction-Guided Forgery Localization

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IEEE Transactions on Consumer Electronics 2025年

作者： Jin, Zehui Zeng, Yangyan Liu, Tenghao Liu, Xinyue Leng, Biao Zhou, Xiaokang Beihang University School of Computer Science and Engineering Beijing100191 China Xiangjiang Laboratory Changsha410205 China Kansai University Faculty of Business Data Science Osaka565-8535 Japan RIKEN RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan

With the popularity of computer vision, many consumer electronic applications now require users to interactively authenticate their identities through cameras while handling business. However, numerous spoofing technologies were proposed in recent years, which enables attackers to perform manipulation during verification. Such manipulations can easily bypass the human-computer-interaction verification, allowing attackers to impersonate others to commit crimes or fraud. Diffusion, as the SOTA generative model, can flexibly reprint image content according to prompt guidance, evading traditional forgery detection techniques. Therefore, there is an urgent need for countermeasures on diffusion manipulation and protects data security of consumer electronics applications. However, existing studies suffer from overfitting specific forgery traces in the training dataset with limited ability on unseen diffusions. In this paper, we propose a novel diffusion-manipulated forgery localization framework leveraging Anomaly-aware Image Reconstruction Deviation(AIRD). Specifically, we train a reconstruction model capable of recovering detailed texture of authentic images, regarding various spoof traces as uniform anomalies and conducts segmentation according to reconstruction deviation. In this case, the proposed method avoids overfitting specific generators, thus achieving better generalization performance in cross-domain scenarios. Extensive experiments on the multiple datasets showcase our effectiveness in extracting general forgery artifacts facing unseen scenarios and diffusion models. © 1975-2011 IEEE.

关键词： Authentication

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DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition

arXiv

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arXiv 2023年

作者： Guan, Shannan Yu, Xin Huang, Wei Fang, Gengfa Lu, Haiyan Australia Artificial Intelligence Institute University of Technology Sydney Australia School of Information Technology and Electrical Engineering University of Queensland Australia RIKEN Center for Advanced Intelligence Project Tokyo Japan School of Electrical and Data Engineering University of Technology Sydney Australia

In this work, we propose a new Dual Min-Max Games (DMMG) based self-supervised skeleton action recognition method by augmenting unlabeled data in a contrastive learning framework. Our DMMG consists of a viewpoint variation min-max game and an edge perturbation min-max game. These two min-max games adopt an adversarial paradigm to perform data augmentation on the skeleton sequences and graph-structured body joints, respectively. Our viewpoint variation min-max game focuses on constructing various hard contrastive pairs by generating skeleton sequences from various viewpoints. These hard contrastive pairs help our model learn representative action features, thus facilitating model transfer to downstream tasks. Moreover, our edge perturbation min-max game specializes in building diverse hard contrastive samples through perturbing connectivity strength among graph-based body joints. The connectivity-strength varying contrastive pairs enable the model to capture minimal sufficient information of different actions, such as representative gestures for an action while preventing the model from overfitting. By fully exploiting the proposed DMMG, we can generate sufficient challenging contrastive pairs and thus achieve discriminative action feature representations from unlabeled skeleton data in a self-supervised manner. Extensive experiments demonstrate that our method achieves superior results under various evaluation protocols on widely-used NTU-RGB+D and NTU120-RGB+D datasets. Copyright © 2023, The Authors. All rights reserved.

关键词： Musculoskeletal system

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Data Freshness Performance Analysis in NOMA-Enabled Green Mobile Crowdsensing

Data Freshness Performance Analysis in NOMA-Enabled Green Mo...

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IEEE International Conference on Communications (ICC)

作者： Yaoqi Yang Bangning Zhang Daoxing Guo Renhui Xu Lin Ge Weizheng Wang Xiaokang Zhou Communication Engineering School Army Engineering University Nanjing China Department of Computer Science City University of Hong Kong China Faculty of Data Science Shiga University Hikone Japan The RIKEN Center for Advanced Intelligence Project RIKEN Tokyo Japan

Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario.

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Generalizing consistent multi-class classification with rejection to be compatible with arbitrary losses 22

Generalizing consistent multi-class classification with reje...

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Yuzhou Cao Tianchi Cai Lei Feng Lihong Gu Jinjie Gu Bo An Gang Niu Masashi Sugiyama School of Computer Science and Engineering Nanyang Technological University Singapore Ant Group China College of Computer Science Chongqing University China and RIKEN Center for Advanced Intelligence Project Japan RIKEN Center for Advanced Intelligence Project Japan RIKEN Center for Advanced Intelligence Project Japan and The University of Tokyo Japan

ISBN: (纸本)9781713871088

Classification with rejection (CwR) refrains from making a prediction to avoid critical misclassification when encountering test samples that are difficult to classify. Though previous methods for CwR have been provided with theoretical guarantees, they are only compatible with certain loss functions, making them not fexible enough when the loss needs to be changed with the dataset in practice. In this paper, we derive a novel formulation for CwR that can be equipped with arbitrary loss functions while maintaining the theoretical guarantees. First, we show that K-class CwR is equivalent to a (K +1)-class classification problem on the original data distribution with an augmented class, and propose an empirical risk minimization formulation to solve this problem with an estimation error bound. Then, we find necessary and sufficient conditions for the learning consistency of the surrogates constructed on our proposed formulation equipped with any classification-calibrated multi-class losses, where consistency means the surrogate risk minimization implies the target risk minimization for CwR. Finally, experimental results validate the effectiveness of our proposed method.

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