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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Yuanzheng Tan Yusi Long Songhan Zhao Shimin Gong Dinh Thai Hoang Dusit Niyato School of Intelligent Systems Engineering Sun Yat-sen University China School of Electrical Engineering Yanshan University China Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology China School of Electrical and Data Engineering University of Technology Sydney Australia School of Computer Science and Engineering Nanyang Technological University Singapore

In this paper, we consider an IRS-assisted and wireless-powered mobile edge computing (MEC) system that allows both edge users and the IRS to harvest energy from the hybrid access point (HAP), co-located with the MEC server. Each edge user uses the harvested energy to offload its data to the MEC server. The IRS not only assists downlink energy transfer to the edge users, but also improves the users' uplink offloading rates. To minimize the overall energy consumption, we jointly optimize the users' offloading decisions, the HAP's active beamforming, as well as the IRS's energy harvesting and passive beamforming strategies. The energy minimization problem is intractable due to complicated couplings in both the objective function and constraints. We decompose this problem into the downlink energy transfer and the uplink data offloading phases. The uplink phase can be efficiently optimized by the conventional semi-definite relaxation (SDR) method, while the downlink phase depends on the alternating optimization between the users' offloading decisions and the joint active and passive beamforming strategies. Numerical results demonstrate that the proposed offloading scheme can significantly reduce the HAP's energy consumption compared with typical benchmarks.

关键词： Wireless communication Energy consumption Array signal processing Energy exchange Minimization Downlink Servers

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A new presentation of the Indian Ocean shallow overturning circulation from a vertical perspective

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Atmospheric and Oceanic Science Letters 2021年第5期14卷 56-61页

作者： Tiecheng Zhang Weiqiang Wang Qiang Xie Kexiu Liu Dongxiao Wang Xinrong Wu Xiaoshuang Zhang Kang Xu Wenya Yuan Key Laboratory of State Oceanic Administration for Marine Environmental Information Technology National Marine Data and Information ServiceMinistry of Natural ResourcesTianjinChina State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhouChina Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) GuangzhouChina Innovation Academy of South China Sea Ecology and Environmental Engineering Chinese Academy of SciencesGuangzhouChina Institute of Deep-sea Science and Engineering Chinese Academy of SciencesSanyaChina Center for Ocean Mega-Science Chinese Academy of SciencesQingdaoChina School of Marine Sciences Sun Yat‐Sen UniversityZhuhaiChina

The calculation of the meridional overturning streamfunction in the southern Indian Ocean is biased by the Indonesian ***,this study applies the vertical overturning streamfunction to diagnose the shallow overturning circulation in the Indian *** the Ocean General Circulation Model for the Earth simulator output,improvements with the vertical overturning streamfunction compared with the meridional overturning streamfunction are *** results show that the vertical overturning streamfunction smoothly connects the shallow overturning circulations of the northern Indian Ocean and the southern Indian Ocean with the whole cycle of the subtropical cell and the cross-equatorial *** vertical overturning streamfunction shows a much cleaner shallow overturning circulation,which is underestimated by the meridional overturning *** shows that the shallow overturning circulation has a magnitude of~13 Sv(1 Sv≡106 m 3 s−1),of which the subtropical cell accounts for~8 *** addition,the vertical overturning streamfunction captures a clockwise overturning cell in the upper 600 m layer between 30°S and 34°*** cell has a magnitude of about−5 Sv and probably corresponds to the wind-forced subtropical ***,the vertical overturning streamfunction provides a new approach for estimating the shallow overturning circulation in the Indian Ocean.

关键词： Indian Ocean Shallow overturning circulation Meridional overturning streamfunction Vertical overturning streamfunction

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Web Log Analysis in Genealogy System

Web Log Analysis in Genealogy System

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IEEE International Conference on Big knowledge (ICBK)

作者： Xiaojian Liu Yi Zhu Shengwei Ji Ministry of Education Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

A large amount of log data is generated every moment in many real-world applications. System logs, mobile application logs, web logs etc., all of which contain rich information and can be analyzed for valuable information. At the same time, genealogy attracts more and more attention in recent decades, especially for Chinese. People utilize the genealogy system to seek roots, find source of family, build a family tree and so on. Due to the complexity of genealogy data and specific features of genealogy system, how to extract and analyze the valued genealogy information effectively is a huge challenge. Motivated by this, we propose a novel analysis method using web logs in genealogy system for drawing user profile and providing personalized recommendations. More specifically, firstly, all web logs are extracted from genealogy system based on the enhanced logs which record the behaviors and data of user. Secondly, the extracted logs are formatted for analysis, and we analyze the logs to extract various user-related attributes for drawing user profile. Finally, personalized recommendations like interested people and family tree are provided for each user in system. The high availability and effectiveness of our proposed method is verified on genealogy system-Huapu system.

关键词： data mining databases data visualization Tools Big data Feature extraction knowledge engineering

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Editorial: engineering applications of neurocomputing, volume II

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Frontiers in Neurorobotics 2023年 17卷 1306042页

作者： Wang, Long Song, Zhe Zhang, Zijun Huang, Chao School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Business Nanjing University Nanjing China School of Data Science City University of Hong Kong Kowloon Hong Kong State Key Laboratory of Internet of Things for Smart City University of Macau China

The paper titled “Wind speed interval prediction based on the hybrid ensemble model with biased convex cost function” by Long et al. proposed a combination interval prediction based hybrid ensemble model for short-term wind speed prediction. With the benefit of the biased convex cost function and ensemble technique, the high computational efficiency and stable performance of the proposed prediction model was guaranteed simultaneously. The paper titled “Soft-masks guided faster region-based convolutional neural network for domain adaptation in wind turbine detection” by Xu et al. reported a synthetic generation method trying to simulate the real wind turbines from the aspects of style and content.

关键词： neurocomputing engineering systems neural networks manufacturing healthcare

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Denoi-SpEx+: A Speaker Extraction Network based Speech Dialogue System 17

Denoi-SpEx+: A Speaker Extraction Network based Speech Dialo...

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17th IEEE International Conference on e-Business engineering, ICEBE 2021

作者： Hao, Yun Huang, Xiangkang Huang, Huichou Wu, Qingyao School of Software Engineering South China University of Technology Guangzhou China Key Laboratory of Big Data and Intelligent Robot Ministry of Education China Pazhou Lab Guangzhou China University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9781665444187

The speech dialogue system has gradually been widely used in daily life. Users can consult and communicate with the system through natural language. However, in practical applications, third-person background sounds and background noise interference in real dialogue scenes will be encountered. The uncertainty and complexity of these background sounds will have a bad impact on the recognition of the system. A good speech enhancement module can help us to separate the target speaker from the original speech. Recently, a solution called SpEx+ was proposed from the time domain, but SpEx+ needs a reference speech to assist in training. This reference speech may have noise in actual applications that will affect performance. Therefore, we propose a Denoi-SpEx+ model. Before the reference speech is input to the network, a speech denoising network is added, so that the quality of speech separation in practical applications can be guaranteed. Experiments show that our model can significantly improve the performance of speech separation model of noisy reference speech. © 2021 IEEE.

关键词： Speech enhancement

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Enhancing the generalization of feature construction using genetic programming for imbalanced data with augmented non-overlap degree

Enhancing the generalization of feature construction using g...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Li, Zhuang Qin, Jingyan Gong, Haiyan Zhang, Xiaotong Wan, Yadong University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China School of Mechanical Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan528399 China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9781665401265

Genetic programming (GP) has a significant achievement in feature construction and non-overlap degree can help to improve the generalization ability of GP based feature construction. However, the non-overlap degree is biased towards the majority class. In this paper, a novel GP based feature construction method with augmented non-overlap degree is proposed to enhance the generalization ability for imbalanced data. And the constructed features are evaluated by a novel function based on the combination of the area under the ROC curve metric and the augmented non-overlap degree. The generalization performance is evaluated not only by a particular classification algorithm, but also by six widely used classification algorithms. The experiments conducted on five imbalanced biomedical datasets with different imbalance rates show that the proposed GP-AANO method can achieve superior generalization performance for classification. © 2021 IEEE.

关键词： Genetic programming

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Rule-enhanced Noisy knowledge Graph Embedding via Low-quality Error Detection

Rule-enhanced Noisy Knowledge Graph Embedding via Low-qualit...

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IEEE International Conference on Big knowledge (ICBK)

作者： Yan Hong Chenyang Bu Tingting Jiang Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

knowledge graphs (KGs) have been widely applied in many fields such as recommendation systems and knowledge reasoning. Embedding KGs into a continuous vector space has quickly gained significant attention. However, most traditional KG embedding models assume that all the facts in the existing KGs are completely correct, ignoring that KG construction usually involves automatic mechanisms. These automatic construction processes inevitably generate a lot of noises and conflicts, including low-quality errors (e.g., entity type errors). Moreover, these low-quality noises could greatly influence the quality of rule extraction, which may reduce the efficiency of Rule-Guided Embedding model (RUGE). To address this problem, an efficient method to eliminate those entity type errors in triples is proposed and applied to RUGE. Experimental results demonstrate that the filtering of low-quality noises can greatly improve the accuracy of knowledge representation learning as well as the quality of rules, further illustrating the effectiveness of our method.

关键词： Noise measurement Semantics knowledge representation data mining Predictive models data models

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An Abnormal data Analysis and Processing Method for Genealogy Graph databases

An Abnormal Data Analysis and Processing Method for Genealog...

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IEEE International Conference on Big knowledge (ICBK)

作者： Jianxuan Shao Guliu Liu Shengwei Ji Ministry of Education Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

Large amounts of data are generated continually in the real world. The objects in the data and the relationships between them have become increasingly complex. Graph is a powerful tool for representing these data and the complex relationships between them. To effectively describe the entities and connections in these data, the concept of a knowledge graph was proposed, and knowledge graph has become one of the bases for storing graph data, and the importance of it is self-evident. Genealogy data is a kind of graph data where nodes are used to represent the person in the genealogy data, and edges are used to represent the relationship between the person. Moreover, in a genealogy graph database, the "critical" relationship that is unique for an entity is defined. In contrast, the abnormal data derive from the existence of multiple "critical" relationships between entities. In a genealogy graph, abnormal data will cause the wrong relationships and redundant entities. To avoid such abnormal data in genealogy graph database, the abnormal data are categorized into four different types, and the corresponding processing methods are proposed for each type of abnormal data, respectively. The experiment results demonstrate that the processing method can effectively solve these abnormal data.

关键词： databases Biology Task analysis Anomaly detection data models knowledge engineering Big data

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Discovery of novel mammalian target of rapamycin (mTOR) inhibitors by support vector machine 4

Discovery of novel mammalian target of rapamycin (mTOR) inhi...

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2020 4th International Conference on Energy Material, Chemical engineering and Mining engineering, EMCEME 2020

作者： Wang, Panpan Xu, Xiaobo Li, Yinghong Li, Bo Pei, Qinglan Yu, Pei Jing, Chenxi Lu, Meng College of Chemistry and Pharmaceutical Engineering Huanghuai University Zhumadian China Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Chongqing China College of Life Sciences Chongqing Normal University Chongqing China

Mammalian target of rapamycin (mTOR) is a protein serine/threonine kinase playing the central downstream role in multiple mitogenic signalling pathways. As a c entral regulator of cell growth, proliferation, differentiation and survival, mTOR has b een reported to modulate proliferation and angiogenesis in neoplastic processes. Curre ntly, sirolimus and its analogues the only five mTOR inhibitors approved for clinical u se, which shows a great capacity in anticancer therapy. However, endocrine resistance in cancer therapy has been observed in sirolimus analogues, and the unavailability of n ew mTOR inhibitor besides similar structure of sirolimus analogues makes the resistan ce even worse. It is urgent to discovery new mTOR inhibitors as candidates for develo pment of effective anticancer drugs. In this study, support vector machine (SVM) as a virtual screening strategy was proposed. SVM models of mTOR inhibitors were constr ucted by training data published before 2012, and the ones published after 2012 as test set were used to verify according to cross validation. The selected model performed thi n false hit rates of 0.12% and 0.46% by screening PubChem and MDDR chemical libr aries respectively. As results, 9 novel novel scaffolds for mTOR were identified, and 6 of them have been reported their anticancer-related therapeutic capacity. In summary, SVM performed its ability to identify novel mTOR inhibitors, which can supply some candidates for mTOR anticancer drugs, and supply effective method for anticancer dru g discovery in future. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Support vector machines

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MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARNING

arXiv

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arXiv 2023年

作者： Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Li, Minghui Zhang, Leo Yu Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab China

Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels in parallel execution capabilities, while the latter enjoys low dependence on edge computing resources and strong privacy protection. Split federated learning (SFL) combines the strengths of both FL and SL, making it one of the most popular distributed architectures. Furthermore, a recent study has claimed that SFL exhibits robustness against poisoning attacks, with a fivefold improvement compared to FL in terms of robustness. In this paper, we present a novel poisoning attack known as MISA. It poisons both the top and bottom models, causing a misalignment in the global model, ultimately leading to a drastic accuracy collapse. This attack unveils the vulnerabilities in SFL, challenging the conventional belief that SFL is robust against poisoning attacks. Extensive experiments demonstrate that our proposed MISA poses a significant threat to the availability of SFL, underscoring the imperative for academia and industry to accord this matter due attention. Copyright © 2023, The Authors. All rights reserved.

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