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5th European conference on Space Debris

作者： Molotov, I. Agapov, V. Kouprianov, V. Titenko, V. Rumyantsev, V. Biryukov, V. Borisov, G. Burtsev, Yu. Khutorovsky, Z. Kornienko, G. Erofeeva, A. Litvinenko, E. Aliev, A. Zalles, R. Grebetskaya, O. Likh, Yu. Rusakov, O. Minikulov, N. Guliamov, M. Abdulloev, B. Borisova, N. Irsmambetova, T. Vikhristenko, A. Inasaridze, R. Gubin, E. Erofeev, A. Ivaschenko, Yu. Yurkov, V. Matkin, A. Rybak, A. Karaush, D. Letsu, A. Tsibizov, O. Ermakov, B. Siniakov, E. Keldysh Institute of Applied Mathematics Miusskaja sq. 4 Moscow 125047 Russia Astronomical Observatory Pulkovskoe chaussee 65/1 St.-Petersburg 196140 Russia JSC Vimpel International Corporation 4th street of 8 Marta 3 Moscow 125319 Russia Zverev Krasnogorsky Zavod Rechnaya str. 8 Krasnogorsk-7 143400 Russia Scientific-research Institute Crimean Astrophysical Observatory Nauchny 98409 Ukraine Crimean Laboratory of Shtenberg Astronomical Institute Nauchny 98409 Ukraine Space Force of Russian Ministry of Defense Miasnitskaya37 Moscow 105175 Russia Ussuriysk Astrophysical Observatory Gornotaeznoe 692533 Primorsky Kray Russia Ulugh Beg Astronomical Institute Astronomicheskaya str. 33 Tashkent 700052 Uzbekistan Observatorio Astronomico Nacional Casilla 346 Tarija Bolivia Institute of Astrophysics Bukhoro str. 22 Dushanbe 734042 Tajikistan Shevchenko Pridnestrovskiy State University 25 October str. 128 Tiraspol 734042 Moldova Georgian National Astrophysics Observatory Kazbegi 2-a Tbilisi 0160 Georgia Scientific-research Institute Astronomical Observatory of Mechnikov Odessa National University Ilpha and Petrova str. 55/1 Odessa 65122 Ukraine Andrushivka Astronomical Observatory Andrushivka 13400 Zhitomirskaya Oblast Ukraine

ISBN: (纸本)9789292212360

the international scientific optical network (ISON) that was developed in the last few years is one from largest system specialized on space debris observations at high orbits and is able to observe whole GEO ring. Now ISON collaborates with 25 observatories in 9 countries. Series of standard telescopes and mounts was produced, and a lot of the modern CCD cameras is purchased to equip the ISON observatories. Standard solution for precise time keeping is installed at each telescope together with standard software packages for CCD frame processing, CCD camera, GPS receiver and mount control. 32 telescopes with aperture in range between 0.2 and 2.6 m are arranged in the three ISON subsets dedicated to different class objects. the ISON observations are coordinated mainly by the Center on collection;processing and analysis of information on space debris (CCPAISD) developed and operated on the basis of the Ballistic Centre at the KIAM, Russian Academy of Sciences. Almost one million measurements about 2000 space objects were received at CCPAISD up to now. More than 700 earlier unknown objects are discovered. It is planned to obtain about two millions measurements per year since 2009. ISON is an open international non-government project and may be considered as a free source of information on space objects for global civil SSA.

关键词： CCD cameras

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Sequence-to-Sequence Multi-Hop Knowledge Reasoning Based on Retentive Network

Sequence-to-Sequence Multi-Hop Knowledge Reasoning Based on ...

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Computer Information Science and Application Technology (CISAT), international conference on

作者： Ruilin Su Wanshan Zhang Dunhui Yu Hubei University Wuhan China Wuhan China School of Computer Science and Information Engineering Hubei University Wuhan China Hubei Key Laboratory of Big Data Intelligent Analysis and Application Hubei University Wuhan China Engineering and Technical Research Center of Hubei Province in Software Engineering Wuhan China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

Multi-hop Knowledge Reasoning is a task that involves generating an answer given a query and a knowledge graph. Existing sequence-to-sequence reasoning models use the Transformer to encode and decode sequences, but these models have some flaws, such as the inability to effectively handle long-sequence reasoning and susceptibility to exposure bias. To address these issues, we provides a sequence-to-sequence reasoning model named STSR, which is based on Retentive Network. Aiming at improving training efficiency through parallel training, this model leverages the advantages in Retentive Network, reduce time overhead, and enhance reasoning efficiency through iterative reasoning. It effectively mitigates the problems of high spatial overhead and low efficiency in long-sequence reasoning faced by the Transformer. Moreover, it retains and updates historical information during the encoding and decoding process, enhancing the model’s memory and generalization capabilities. Additionally, the Scheduled Sampling method is adopted to alleviate the exposure bias introduced during reasoning, which involves using the model’s own output as the input for the next moment with a certain probability during training, instead of using the true label. We conduct the experiment on six public datasets, with the results showing that the proposed model outperforms existing baseline models in terms of precision and generation quality. this paper provides a new solution for the task of sequence-to-sequence multihop knowledge reasoning and also demonstrates the potential application of the Retentive Network in natural language processing.

关键词： Training Knowledge engineering Accuracy Spread spectrum communication Knowledge graphs Transformers Sampling methods Cognition Natural language processing Iterative decoding

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Plasmonic flow-through biosensor using a polymeric substrate

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JOURNAL OF MICROMECHANICS AND MICROENGINEERING 2014年第3期24卷

作者： Buchenauer, Andreas Bialon, Magdalena Segun, Daniel Puettmann, Christiane Stein, Christoph Barth, Stefan Schnakenberg, Uwe Rhein Westfal TH Aachen Inst Mat Elect Engn 1 D-52074 Aachen Germany Rhein Westfal TH Aachen Dept Expt Med & Immunotherapy Inst Appl Med Engn D-52074 Aachen Germany Fraunhofer IME Dept Pharmaceut Prod Dev D-52074 Aachen Germany

Substrates for plasmonic sensors in a flow-through configuration are mostly fabricated by cost-intensive clean room processes, whereas high-volume diagnostic devices are typically made of polymers. this contrast could limit the application of this efficient flow regime in mass-produced devices. In order to become more compatible with polymer processing, a commercially available polycarbonate filter membrane has been evaluated as a substrate for plasmonic flow-through biosensing. the membrane has been sputtered with gold and its sensitivity to changes of bulk refractive index has been determined by transmission measurements using sodium chloride solutions. the sensitivity has been evaluated by determining the wavelength barycenter in a wavelength interval from 470 to 800 nm. the highest determined sensitivity to variations in bulk refractive index is 117 nm RIU-1 (refractive index units). this sensitivity is smaller than that of regular arrays of nanoholes. But the integrating character of the applied evaluation leads to an average standard deviation of 0.005 nm which results in a resolution of 4.1 . 10(-5) RIU. this resolution is sufficient for the detection of protein adsorptions. the proof of principle has been shown with bovine serum albumin and a simplified immunoassay, which consists of the sequential addition of protein A, an IgG antibody and its corresponding antigen. the results show the applicability of this polymeric membrane for biosensing applications. these substrates could enable plasmonic sensing in a flow-through configuration in disposable diagnostic devices.

关键词： biosensor surface plasmon resonance flow-through polymer

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Stereo Matching Algorithm Based on DACVNet

Stereo Matching Algorithm Based on DACVNet

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international conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Lixin Zhao Xu Wang Fanliang Bu Yao Zhou Lin Tan People's Public Security University of China Beijing China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Stereo matching is the most important step in binocular vision 3D reconstruction, and the matching effect directly affects the result of 3D reconstruction. In this paper, ACVNet is used as the benchmark network, and the network model is improved. the reference network uses the three-layer ResNet structure in the image classification task in the process of feature extraction, and there are some problems such as insufficient edge and texture information extraction and inaccurate feature information extraction. To solve these problems, based on ACVNet, a lightweight DFA module is introduced, which is more suitable for feature extraction in stereoscopic matching tasks. Considering the poor effect of the fine texture region, an inter-dimensional multi-scale module is introduced into the construction of the matching cost, and the feature map obtained after feature extraction is processed to enhance the effect of the weak texture region. the parallax completion module and parallel multi-scale module are introduced into the cost aggregation to reduce the errors in the occlusion region and obtain a denser high-precision parallax map. the results of training and evaluation on SceneFlow, KITTI2012 and KITTI2015 data sets show that the accuracy of the proposed improved algorithm is improved compared with the benchmark model. Finally, the three-dimensional matching method is used to reconstruct the real scene, and good results are obtained.

关键词： Training Solid modeling Costs three-dimensional displays Accuracy Stereo image processing Benchmark testing Feature extraction Information retrieval Information systems

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Formal Modeling and Analysis of Transaction Scheduling and Concurrency Control in Grid Databases

Formal Modeling and Analysis of Transaction Scheduling and C...

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Asia Simulation conference 2008/the 7th international conference on System Simulation and Scientific Computing（ICSC‘2008）

作者： Yaojun Han College of international Business,Shanghai international Studies University,Shanghai,200083 CHINA Changjun Jiang Department of Computer Science & Engineering,Tongji University,Shanghai,200092,CHINA Xumei Luo College of international Finance and Trade,Shanghai international Studies University,Shanghai,200083 CHINA

Transaction scheduling and concurrency control are two important problems in a distributed environment. A lot of research has been focused on the problems recently, and many models and measures have been proposed. However, some of them didn't fit for grid environment, as grid architecture is a new and distinguished from conventional distributed computing by its heterogeneous, dynamic and autonomous properties. In this paper, we propose a three-level transaction scheduling model for grid database, which not only shows the autonomy of grid but also lightens the pressure of communication and grid scheduler. We consider communication time of a transaction, user's priority and the number of DB sites accessed by the transaction as a priority of the transaction, and give scheduling algorithms for concurrency transaction, which not only supports correctness of the data, but also improves the effectiveness of the system. Petri nets are promising tools for modeling and analysis information processing systems that are characterized as being concurrent, parallel and distributed. We use a dynamic time colored Petri net (DTCPN) to model each level's transaction scheduling and get a DTCPN model for three-level transaction scheduling model of grid database using sharing composition. Finally, we get some important results such as miss rate of transactions by analyzing reachability of Petri nets.

关键词： net Petri Formal Modeling and Analysis of Transaction Scheduling and Concurrency Control in Grid Databases

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the Method of Intelligent Inspection of Product Quality Based on Computer Vision

The Method of Intelligent Inspection of Product Quality Base...

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the 7th international conference on Computer-Aided Industrial Design and Conceptual Design (CAID&CD’2006)

作者： YAN Tai-shan 1,2 CUI Du-wu 1 (1. Institute of Automation Science, Xi’an University of Technology, Xi’an, Shaanxi 710048) (2.Department of Computer Science, Hunan Institute of Technology, Yueyang, Hunan 414000)

the technique of automated visual inspection is a new development in computer inspection. It has many advantages such as no touching with inspected objects, high speed, high efficiency and good flexibility, etc.. So it has extensive applied foreground in the modern automatic inspection of product quality. this paper introduces the general structure of the computer vision inspection system, expounds the realization method of an on-line crack inspection system of glass bottles, which combines with neural network principle. the system's ability to learn itself and adapt itself is very powerful, it has realized a quick and exact inspection of the on-line glass bottles' crack successfully.

关键词： Product Quality Technique of Automated Visual Inspection Neural Network Image Collecting Image processing

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the opportunities and constraints in using cost-effective satellite remote sensing for biodiversity monitoring

The opportunities and constraints in using cost-effective sa...

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OCEANS

作者： W. Crosse Conservation International India

In February 2004 the 7th conference of the parties for the Convention on Biological Diversify recommended the implementation of a set of indicators to measure progress towards the 2010 and 2025 target of significantly reducing the loss of terrestrial and marine biological diversity. Collaboration between local, national and international networks is now currently being formed to measure these indicators and the resulting success of investing conservation practices into threatened areas. By measuring changing levels in the status of biodiversity, at interrelated ecological scales, the conservation community can better evaluate the success of conservation action. Analogous to the terrestrial system we hypothesise that satellite remote sensing instruments are potentially very useful tools for detecting change in the distribution of key coastal habitats and thus can be applied to monitor the spatial degradation of coral reefs, sea grass beds, mangroves and kelp forests. Using cost-effective platforms accompanied by supervised classification and images processing tools, we believe that there is an opportunity to utilise these systems to measure the status of marine habitats on a national, regional and global scale of effort. Remote sensing tools will continue to increase in accuracy, decrease in cost and become more accessible to the conservation community. As this happens the opportunity' to overlay global habitat survey images in a time series manner will become greater.

关键词： Remote monitoring Satellites Biodiversity Sea measurements Loss measurement international collaboration Area measurement Current measurement Instruments Degradation

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Prediction of irrigation water requirement based on parallel CNN-LSTM model and Mann-Kendall test

Prediction of irrigation water requirement based on parallel...

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Industrial Cyber-Physical Systems (ICPS)

作者： Hao Wen Haochen Ma Yu Du Jinchao Zhang Li He College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China Dongshen Intelligent Water Technology Company LTD Shenzhen China

ISBN: (数字)9798350363012

ISBN: (纸本)9798350363029

Accurate prediction of irrigation water requirement is the basis for irrigation water conservation. However, the widely used machine learning prediction methods do not utilize spatiotemporal information between related features effectively, and the abrupt mutation data processing method for environmental factors requires improvement. this study proposes an irrigation water requirement prediction method using a parallel Convolutional Neural Network (CNN) and Long Short-Term Memory network (LSTM) based on the Mann-Kendall test. In this study, the non-stationary data is segmented into subsequences based on the mutation points of meteorological data detected by the Mann-Kendall test. then, to satisfy the requirement of extracting the spatiotemporal information of input features, a parallel CNN-LSTM network is built. the CNN is used to reextract and down-sample the spatial information of features. Furthermore, the LSTM network is used for regression fitting in the time dimension to realize farmland irrigation water requirement prediction. Compared with CNN, LSTM, and CNNLSTM with data from 2020 to 2023 in Beijing, the results show that the proposed model can effectively improve the accuracy and stability of irrigation water requirement prediction. this study can provide a reference for intelligent water-saving irrigation and optimal allocation of water resources in irrigation areas.

关键词： Irrigation Accuracy Predictive models Water conservation Data models Stability analysis Convolutional neural networks

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Using Chou's Pseudo Amino Acid Composition for Protein Remote Homology Detection

Using Chou's Pseudo Amino Acid Composition for Protein Remot...

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the 7th international conference on Management and Service Science(MASS 2013)

作者： Bin Liu Xiaolong Wang School of Computer Science and Technology Harbin Institute of TechnologyShenzhen Graduate School Key Laboratory of Network Oriented Intelligent Computation Harbin Institute of TechnologyShenzhen Graduate School Shanghai Key Laboratory of Intelligent Information Processing

Protein remote homology detection is a key problem in ***,the discriminative methods,such as Support Vector Machine(SVM),can achieve the best *** most efficient approach to improve the performance of the SVM-based methods is to find a general protein representation method that is able to convert proteins with different lengths into fixed length vectors and captures the different properties of the proteins for the *** bottleneck of designing the protein representation method is that native proteins have different *** by the success of the pseudo amino acid composition(PseAAC) proposed by Chou,we applied this approach for protein remote homology *** new indices derived from the amino acid index(AAIndex) database are incorporated into the PseAAC to improve the generalization ability of this *** experiments on a well-known benchmark show this method achieves superior or comparable performance with current state-of-the-art methods.

关键词： Protein Remote Homology Support Vector Machine Pseudo Amino Acid Composition Protein Representation

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AE-Conv MLP: A Lightweight Convolutional MLP for Age Estimation

AE-Conv MLP: A Lightweight Convolutional MLP for Age Estimat...

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Machine Learning and Natural Language processing (MLNLP), international conference on

作者： Xi Du Rui Li Qiang Gu Jian Zhang Cheng Sun Qian Zhou Rui Chen Li Wang Shangqi Wang China Mobile Nanjing China

ISBN: (数字)9798350354973

ISBN: (纸本)9798350354980

Age estimation from facial images is an attractive research topic in computer vision. A variety of large and deep Convolutional Neural Networks (CNN) based approaches have been proposed with promising performance. However, these models are not suitable for deploying on mobile platforms with limited resources. In response to this weakness, we propose AE-ConvMLP, a lightweight Convolutional Multi-Layer Perceptions (MLP) architecture for Age Estimation, which can be effectively applied to mobile and embedded devices. Inspired by the long-range modeling ability of MLP, AE-ConvMLP integrates the strengths of CNN and vision MLP to capture both short-range and long-range visual dependencies. Concretely, the depthwise convolution is employed to capture essential local visual cues, and a novel Fully Connected (FC) layer named Global Region FC (GRFC) is proposed to efficiently aggregate global visual dependencies by a sparse token partition strategy. To achieve a stable learning, we propose a new loss named Gaussian Error loss, in which the difference between the predicted and the ground-truth value is regarded as a distribution rather than a discrete value to enhance stability at the training stage. Finally, we optimize our network in a joint learning fashion by performing regression and label distribution learning simultaneously. Extensive experiments on several commonly-evaluated age estimation datasets are performed. Our AE-ConvMLP achieves state-of-the-art performance among small models with lower complexity and outperforms some large models by a relatively large margin with only 1/300 parameters and 1/1519 FLOPs.

关键词： Training Performance evaluation Visualization Estimation Machine learning Stability analysis Natural language processing Complexity theory Convolutional neural networks Standards

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