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3rd International Conference on Electrical, Computer and Communication engineering, ECCE 2023

作者： Alam, Khorshed Nigar, Nishargo Erler, Heidy Banerjee, Anonnya United International University Computer Science & Engineering Dhaka Bangladesh Co-Founder Bolo Hamburg Germany Hamburg University of Technology Information & Communication Systems Hamburg Germany

ISBN: (纸本)9798350345360

Speech Emotion Recognition (SER) is an act of recognizing human emotion and affective states from speech. This is because voice often reflects underlying emotion through tone and pitch. Emotion recognition is a component of speech recognition which is gaining more popularity and need for it is increasing exceptionally. Our paper aims to use the Feedforward Neural Network to recognize emotions from unseen data (i.e., audio files) and label them according to the range of different emotions using appropriate variables (such as modality, emotion, intensity, repetition etc.) found in the data. This approach can be particularly useful in the case of identifying the inherent emotion behind human voice. © 2023 IEEE.

关键词： Emotion Recognition

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Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

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Synthetic and systems Biotechnology 2023年第3期8卷 498-508页

作者： Yalun Wu Qianqian Yuan Yongfu Yang Defei Liu Shihui Yang Hongwu Ma State Key Laboratory of Biocatalysis and Enzyme Engineering School of Life SciencesHubei UniversityWuhan430062HubeiChina Biodesign Center Key Laboratory of Systems Microbial BiotechnologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjin300308China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhan430062HubeiChina Artificial Intelligence and Knowledge Engineering Lab School of Computer Science and Information EngineeringHubei UniversityWuhan430062HubeiChina

High-quality genome-scale metabolic models(GEMs)could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology *** of the constant establishment and update of GEMs for model microorganisms such as Escherichia coli and Saccharomyces cerevisiae,high-quality GEMs for non-model industrial microorganisms are still *** mobilis *** ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical *** five GEMs of *** have been constructed,these models are either generating ATP incorrectly,or lacking information of plasmid genes,or not providing standard format *** this study,a high-quality GEM iZM516 of *** ZM4 was *** information from the improved genome annotation,literature,datasets of Biolog Phenotype Microarray studies,and recently updated Gene-Protein-Reaction information was combined for the curation of ***,516 genes,1389 reactions,1437 metabolites,and 3 cell compartments are included in iZM516,which also had the highest MEMOTE score of 91%among all published GEMs of *** growth was then predicted by iZM516,which had 79.4%agreement with the experimental results of the substrate *** addition,the potential endogenous succinate synthesis pathway of *** ZM4 was proposed through simulation and analysis using ***,metabolic engineering strategies to produce succinate and 1,4-butanediol(1,4-BDO)were designed and then simulated under anaerobic condition using *** results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies,which was comparable to that of the model species *** study thus not only established a high-quality GEM iZM516 to help understand and design microbial cell fac

关键词： Genome-scale metabolic models(GEMSs) Non-model industrial microorganism Zymomonas mobilis Biolog phenotype microarray Succinate 1,4-Butanediol

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ANIMC: A Soft Approach for Autoweighted Noisy and Incomplete Multiview Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2022年第2期3卷 192-206页

作者： Fang, Xiang Hu, Yuchong Zhou, Pan Wu, Dapeng Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering The School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Information Storage System Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Multiview clustering has wide real-world applications because it can process data from multiple sources. However, these data often contain missing instances and noises, which are ignored by most multiview clustering methods. Missing instances may make these methods difficult to use directly, and noises will lead to unreliable clustering results. In this article, we propose a novel autoweighted noisy and incomplete multiview clustering (ANIMC) approach via a soft autoweighted strategy and a doubly soft regular regression model. First, by designing adaptive semiregularized nonnegative matrix factorization, the soft autoweighted strategy assigns a proper weight to each view and adds a soft boundary to balance the influence of noises and incompleteness. Second, by proposing θ-norm, the doubly soft regularized regression model adjusts the sparsity of our model by choosing different θ. Compared with previous methods, ANIMC has three unique advantages: 1) it is a soft algorithm to adjust our approach in different scenarios, thereby improving its generalization ability;2) it automatically learns a proper weight for each view, thereby reducing the influence of noises;3) it performs doubly soft regularized regression that aligns the same instances in different views, thereby decreasing the impact of missing instances. Extensive experimental results show its superior advantages over other state-of-the-art works. © 2020 IEEE.

关键词： Clustering algorithms

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A Systematic Approach to Predict Anemia from Eye Conjunctiva Images 26

A Systematic Approach to Predict Anemia from Eye Conjunctiva...

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26th International Conference on Computer and information technology, ICCIT 2023

作者： Noor, Nahiyan B. Oyshi, Uttamasha A. Das, Avishek Iqbal, Kamran University of Arkansas Information Science Little Rock United States University of Arkansas Computer Science Little Rock United States Chittagong University of Engineering and Technology Systems Engineering Chattogram4349 Bangladesh University of Arkansas Computer Science & Engineering Little Rock United States

ISBN: (纸本)9798350359015

Anemia is a health condition that occurs when there is insufficient hemoglobin (Hb) in the bloodstream. Although not usually lethal in mild cases, in severe cases, it can be life-threatening, especially for women, as it can lead to premature birth during pregnancy, heart problems, and multi-organ failure resulting in death. Anemia is a disease that can be easily cured if caught early, however, patients often ignore symptoms like fatigue, headache, or shortness of breath. Diagnosis of anemia requires a CBC blood test or a physical examination done by a healthcare professional, which can be both costly and time-consuming. The main aim of the current study is to propose a non-invasive and efficient method to diagnose anemia, which can be done by taking images of the eye conjunctiva. The raw image data corresponding to anemic conditions and blood hemoglobin levels (BHL) were collected from three distinct clinical sources. After preprocessing and cleaning the images, 18 features in 3 different color spaces were extracted. Using those features, anemia was predicted by various machine learning algorithms. The highest detection accuracies of 92% were observed with an ensemble of Support Vector Classifier, Random Forest, Logistic Regression, and *** Relevance-Anemia affects approximately 25% of the world's population. This study suggests a non-invasive method for predicting anemia using images of the eye conjunctiva, which eliminates the need for any blood tests. © 2023 IEEE.

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Angular Properties for Power from a Spatial Cluster

Angular Properties for Power from a Spatial Cluster

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European Conference on Antennas and Propagation, EuCAP

作者： Torbjörn Ekman Department of Electronic Systems Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A spatial cluster of scatterers, which forms a link between a transmitter and a receiver, behaves as a random array that passively relays the radio signal. The statistical properties of the antenna pattern for this random array are derived in the far field. The analysis is performed for circularly symmetric clusters with independent and uniformly distributed phases for the scattering events. The average lobe width, the average notch width, and the number of level crossings for the antenna pattern are derived for a Gaussian spatial cluster. The simulation of the cluster properties coincides with the analytical results.

关键词： Graphical models Wavelength measurement Radio transmitters Scattering Receivers Radio propagation Size measurement Relays Standards Antenna arrays

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Efflcient machining of a complex blisk channel using a disc cutter

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Chinese Journal of Aeronautics 2024年第1期37卷 414-437页

作者： Xiangyu LI Zhaoyu LI Dong HE Junxue REN Qian FENG Kai TANG Department of Mechanical and Aerospace Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Key Laboratory of High Performance Manufacturing for Aero Engine(Northwestern Polytechnical University) Ministry of Industry and Information TechnologyXi’an 710072China Xi’an Sanhang Power Technology Co. LtdXi’an 710000China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute FutianShenzhen 518057China HKUST Shenzhen Research Institute Shenzhen 518057China

For rough machining of a complex narrow cavity,e.g.,a complex blisk channel on an aero-engine,the typically used cutting tools are the slender cylindrical cutter and conical ***,as neither of the two is particularly suited for rough machining,wherein the main purpose is to remove a large volume as quickly as possible,the machining efficiency is low,especially when the part materials are of hard-to-cut types(e.g.,Titanium-alloy)for which it often takes days to rough machine a ***,disc machining provides a new and efficient roughing solution,since a disc cutter with a large radius enables a much larger cutting speed and thus a larger material removal ***,due to the large radius of the disc cutter,its potential collision with narrow and twisted channels becomes a serious *** this paper,we propose a novel twophase approach for efficiently machining a complex narrow cavity workpiece using a disc-shaped cutter,i.e.,3+2-axis disc-slotting of the channel by multiple layers(rough machining)+five-axis disc-milling of the freeform channel side surfaces(semi-finish machining).Both simulation and physical cutting experiments are conducted to assess the effectiveness and advantages of the proposed *** experimental results show that,with respect to a same cusp-height threshold on the channel side surfaces,the total machining time of the tested part by the proposed method is about only 36%of that by the conventional approach of plunging-milling(for roughing)plus milling by a slender cylindrical cutter(for semi-finishing).

关键词： Blisk channel CNC machining Disc cutter Roughing efficiency Tool path planning

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Carrier-Based UAV Landing via Exploratory Grey Wolf Optimized Model Prediction Control Scheme

Carrier-Based UAV Landing via Exploratory Grey Wolf Optimize...

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International Conference on Guidance, Navigation and Control, ICGNC 2024

作者： Sun, Ning Duan, Haibin Huo, Mengzhen Wu, Hao Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing 100083 China China Academy of Electronics and Information Technology China Electronics Technology Group Corporation Beijing 100041 China

ISBN: (纸本)9789819622115

A carrier-based unmanned aerial vehicle (UAV) landing control system based on nonlinear expanded state observer (NESO) and model predictive controller (MPC) is designed. To compensate for the impact of uncertainty disturbance on control accuracy, NESO is designed, which can effectively estimate the impact of external disturbance on the movement of carrier-based UAV, and exploratory gray wolf optimization is proposed for parameter tuning of the observer. To achieve decoupling between control inputs, MPC is used to establish a carrier-based UAV landing control system. Simulation comparative results demonstrate that the carrier-based UAV control system proposed in the paper performs better than the sliding mode controller scheme that employs a sliding mode observer for landing accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Grey Wolf Optimization Model Predictive Controller Nonlinear Expanded State Observer Unmanned Aerial Vehicle (UAV)

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An Efficient Threshold Ring Signature from G+G Identification Protocol 2nd

An Efficient Threshold Ring Signature from G+G Identificati...

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2nd International Conference on Data Security and Privacy Protection, DSPP 2024

作者： Wu, Chunhui Jiang, Siwei Zhang, Fangguo Du, Yusong Lin, Qiping School of Internet Finance and Information Engineering Guangdong University of Finance Guangzhou510521 China School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Provincial Key Laboratory of Information Security Technology Guangzhou510006 China Xingtang Telecommunication Technology Co. Ltd. Beijing100191 China

ISBN: (纸本)9789819785391

Threshold ring signature confirms that t signers are participating in the signature and keep them anonymous. It is a generalization of ring signature, and has many important applications such as whistleblower, e-voting and blockchain et al. In this paper, an improved lattice-based ring signature and threshold ring signature scheme from Fiat-Shamir heuristic are proposed. The schemes eliminte the dependence on Stern-like identification protocols and have much shorter signature sizes. We also use the Gaussian convolution technique (G+G) presented by Devevey et al. in Asiacrypt 2023 to remove the reject-sampling in BLISS. This allows the threshold ring signature to overcome the proof issue caused by "abort" and achieve higher computation efficiency than previous ones. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication Protocol

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Aqueous production of sulfur-containing aerosols from nitroaromatic compounds and SO2 in wintertime urban haze

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science Bulletin 2025年第11期70卷 1846-1855页

作者： Yang, Ning Wang, Junfeng Jacob, Daniel J. Ye, Jianhuai Sheng, Ming Niu, Mutong Qin, Yiming Ge, Xinlei Sun, Yele Wang, Zifa Wang, Yuhang Wu, Fengchang Liu, Cong-Qiang George, Christian Fu, Pingqing Institute of Surface-Earth System Science School of Earth System Science Tianjin University Tianjin300072 China School of Emergency Management Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing210044 China John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen518055 China School of Energy and Environment City University of Hong Kong Hong Kong999077 China LAPC Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China School of Earth and Atmospheric Sciences Georgia Institute of Technology AtlantaGA02115 United States State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China Université Claude Bernard Lyon 1 CNRS IRCELYON VilleurbanneF-69626 France

Nighttime aqueous oxidation of fossil fuel emissions is a significant source of atmospheric secondary organic aerosols. However, the underlying mechanism of the aqueous processing remains unclear. Utilizing ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry of water-soluble organic carbon samples, we present field observations that reveal the aqueous-phase conversion of nitroaromatic compounds (NACs) and sulfur-containing aerosols from fossil fuel combustion at high relative humidity during a severe haze event in Beijing in the winter of 2016. We have confirmed that the ring-breaking oxidation of NACs can generate nitrous acid in the aqueous phase, which rapidly oxidizes sulfur dioxide (SO2) to sulfate. Subsequently, reactions between sulfate and unsaturated compounds contribute to the formation of aliphatic organosulfates. Our results elucidate a molecular-level understanding of the aqueous production of sulfur-containing aerosols from NACs and SO2 in wintertime urban haze. © 2025 science China Press

关键词： Sulfur dioxide

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Knowledge-based recommendation with contrastive learning

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High-Confidence Computing 2023年第4期3卷 41-46页

作者： Yang He Xu Zheng Rui Xu Ling Tian School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Kash Institute of Electronics and Information Industry Kashgar 844199China China Electronic Technology Cyber Security Co. Ltd.Chengdu 610041China Cyberspace Security Key Laboratory of Sichuan Province Chengdu 610041China

Knowledge Graphs(KGs)have been incorporated as external information into recommendation systems to ensure the high-confidence ***,Contrastive Learning(CL)framework has been widely used in knowledge-based recommendation,owing to the ability to mitigate data sparsity and it considers the expandable computing of the ***,existing CL-based methods still have the following shortcomings in dealing with the introduced knowledge:(1)For the knowledge view generation,they only perform simple data augmentation operations on KGs,resulting in the introduction of noise and irrelevant information,and the loss of essential information.(2)For the knowledge view encoder,they simply add the edge information into some GNN models,without considering the relations between edges and ***,this paper proposes a Knowledge-based Recommendation with Contrastive Learning(KRCL)framework,which generates dual views from user–item interaction graph and ***,through data enhancement technology,KRCL introduces historical interaction information,background knowledge and item–item semantic ***,a novel relation-aware GNN model is proposed to encode the knowledge ***,through the designed contrastive loss,the representations of the same item in different views are closer to each *** with various recommendation methods on benchmark datasets,KRCL has shown significant improvement in different scenarios.

关键词： Knowledge graph Recommendation systems Contrastive learning Graph neural network

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