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Image recognition with extension of neighborhood preserving embedding on matrices

Journal of Information and Computational Science 2012年第6期9卷 1511-1520页

作者： Zhang, Daming Liu, Huayong Li, Lu Luo, Bin Department of Mathematics and Physics Anhui Institute of Architecture and Industry Hefei 230022 China School of Computer Science and Technology Anhui University Hefei 230039 China

Neighborhood Preserving Embedding (NPE) is a novel subspace learning algorithm, which aims at preserving the local neighborhood structure on the data manifold and is a linear approximation to Locally Linear Embedding (LLE). However, in typical image recognition in 1D vectors space, where the number of data samples is smaller than the dimension of data space, suffering from the singularity problem of matrix, NPE algorithm cannot be implemented directly. In this paper, we investigate NPE directly on image matrix for image recognition. The proposed Two-dimensional Neighborhood Preserving Embedding (2DNPE) and bilateral Two-dimensional Neighborhood Preserving Embedding (B2DNPE) algorithms are all based directly on 2D image matrices rather than on 1D vectors as NPE does, thus the problem of singularity confronted in 1D case is overcome. 2DNPE performs compression only in row direction, while B2DNPE performs compression both in row and in column direction. The relation of them to 2DLPP (B2DLPP) are also presented. The proposed algorithms are evaluated on ORL face database and handwritten digits database. © 2012 by Binary Information Press.

关键词： Image recognition

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Sampling Methods for Efficient Training of Graph Convolutional Networks:A Survey

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 205-234页

作者： Xin Liu Mingyu Yan Lei Deng Guoqi Li Xiaochun Ye Dongrui Fan State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100086 School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049 IEEE Department of Precision Instrument Center for Brain Inspired Computing ResearchTsinghua UniversityBeijing 100084China

Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph *** GCN performs well compared with other methods,it still faces *** a GCN model for large-scale graphs in a conventional way requires high computation and storage ***,motivated by an urgent need in terms of efficiency and scalability in training GCN,sampling methods have been proposed and achieved a significant *** this paper,we categorize sampling methods based on the sampling mechanisms and provide a comprehensive survey of sampling methods for efficient training of *** highlight the characteristics and differences of sampling methods,we present a detailed comparison within each category and further give an overall comparative analysis for the sampling methods in all ***,we discuss some challenges and future research directions of the sampling methods.

关键词： Efficient training graph convolutional networks(GCNs) graph neural networks(GNNs) sampling method

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Integrating virtual reality technology into architecture education: the case of architectural history courses

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Open House International 2021年第4期46卷 498-509页

作者： Ibrahim, Anwar Al-Rababah, Amneh Ibrahim Bani Baker, Qanita Department of Architecture Jordan University of Science and Technology Irbid Jordan Department of Computer Science and Software Engineering Jordan University of Science and Technology Irbid Jordan

Purpose: Virtual reality (VR) technology invaded various domains including architecture practice and education. Despite its high applications in architecture design education, VR has a high potential to be used in architectural history courses as well. This paper aims to examine the effect of using VR technology on the students’ learning abilities of history of architecture. Design/methodology/approach: The experimental approach was used. Two experiments were designed by creating virtual environments for two selected architectural examples from the Modern architecture course. The participants who were students of Modern architecture class had to complete two questionnaires, one for each example. The first one was based on Bloom’s taxonomy, and the other was prepared to test the participants’ analytical and critical skills. Besides, participants had to fill out satisfaction and ease-of-use survey on a five-step Likert scale. Findings: Participants in the VR condition achieved better grades in knowledge gain compared to those in the traditional conditions. Their analytical and critical thinking skills were improved in the VR conditions. Gender has a significant impact on analytical and critical thinking skills. Participants recorded a high level of satisfaction;however, male students were more satisfied than female students who reported concerns about the weight of the used tools and nausea symptoms. Research limitations/implications: This study informs architecture education and provides insights into the potentials of using advanced technology in architectural history education. Teaching the various history of architecture courses will be improved, shifted toward a more student-centered curriculum, and may acquire more excitement and conscious curiosity. Originality/value: Using VR in architectural education is rigorous in architectural design courses and students’ design projects’ presentations. This research expands architectural education research by examining ot

关键词： Architectural education Bloom’s taxonomy Built environment tectonics and technologies History of architecture VR technology

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Reliability of complex production systems

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CIVIL ENGINEERING SYSTEMS 1996年第1期13卷 61-73页

作者： Kaplinski, O Milosz, M [a] Faculty of Architecture Civil andEnvironmental Engineering Poznah University of Technology Poznah Poland [b] Department of Computer Science Lublin Technical University Lublin Poland

This paper discusses problems of identifying and estimating the reliability of complex real production systems in the constructing industry. The influence of the system structure on its reliability has been considered. Types of elements and their connections in the system from the point of view of system reliability have been identified. The simulation method presented here allows to investigate the reliability of real systems, including the occurrence of inertia, variability of their structure and mutual dependence of reliability parameters of their elements. Two synthesis algorithms, (considering phase inertial in the estimation of system reliability), have been proposed and compared. On the basis of a machine system (loader-conveyor belt-material receiver), the utilisation of inertia to improve reliability characteristics of the system has been proved to be more effective than adding reserve elements to the system.

关键词： reliability system structure decomposition and synthesis simulation construction operations

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Predicting marital dissolutions using radial basis function neural networks

Predicting marital dissolutions using radial basis function ...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Guillén, A. Tovar, C. Herrera, L.J. Pomares, H. González, J. Guillén, J.F. Rojas, I. Department of Computer Architecture and Technology University of Granada Spain Department of Preventive Medicine University of Granada Spain

ISBN: (纸本)9781424469178

Marital dissolutions, that include divorces and separations, are considered one of the most adverse events that can influence the health, life quality and welfare of the adults and infants implied. There have been several researches in the sanitary and sociological field that show how these processes of breaking a life in common can deteriorate the health in both, the physic and the psychological, aspect. This paper presents the application of machine learning methods to be able to predict if a marriage, that has started a dissolution process, will end up in a friendly agreement or it will be taken to the court. In order to accomplish this task, Radial Basis Function Neural Networks in combination with Mutual Information will be able to determine which elements should be considered to make a prediction. As the experiments will show, the methodology applied is able to classify with a high accuracy and robustness a real data base. The results could be applied in order to prevent some traumas to the people involved in the dissolution in the medical aspect and to perform a better management in the legal aspects. © 2010 IEEE.

关键词： Dissolution

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On-line adaptive fuzzy controller: Application of helicopter stabilization of the altitude of a helicopter

On-line adaptive fuzzy controller: Application of helicopter...

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2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003

作者： Rojas, I. Pomares, H. Puntonet, C.G. Rojas, F. Rodríguez, M. Valenzuela, O. Department of Architecture and Computer Technology University of Granada Spain Department of Applied Mathematics University of Granada Spain

ISBN: (纸本)0780377834

When confronted with a control problem for a complicated physical process, a control engineer generally follows a relatively systematic design procedure. In this paper we design an on-line controller which is able to modify and adapt the rule base of the system with just only qualitative knowledge about the plant to be controlled. In our example, the system is an helicopter, and the objective is to control the altitude of the helicopter, when the mass of the system change, or other parameters defining the helicopter has been modified. © 2003 IEEE.

关键词： Fuzzy control

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HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism

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computers, Materials & Continua 2024年第8期80卷 3351-3377页

作者： TugbaÇelikten Aytug Onan Department of Software Engineering Faculty of TechnologyManisa Celal Bayar UniversityManisa45140Turkey Department of Computer Engineering Faculty of Engineering and ArchitectureIzmir KatipÇelebi UniversityIzmir35620Turkey

Class Title:Radiological imaging method a comprehensive overview *** GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the *** and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed *** recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis ***:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical ***:Radiological imaging is an extremely important tool in modern medicine to assist in medical *** work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.

关键词： Generative artificial intelligence AI-generated text detection attention mechanism hybrid model for text classification

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Linear complexity of sequences produced by single cycle T-function

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The Journal of China Universities of Posts and Telecommunications 2011年第4期18卷 123-128页

作者： WANG Yan HU Yu-pu LI Shun-bo YANG Yang Key Laboratory of Computer Networks and Information Security Ministry of Education Xidian University Xi'an 710071 China Department of Mathematics Xi'an University of Architecture and Technology Xi'an 710055 China

Four kinds of sequences generated by single cycle triangular function （T-function） are investigated to check the possibility for a single cycle T-function to be a cryptographic component in stream ciphers. Based on the special properties of single cycle T-function and an algorithm due to Wei, linear complexities of these four kinds of sequence are all acquired. The results show that single cycle T-function sequences have high linear complexity. Therefore, T-function satisfies the essential requirements being a basic component of stream cipher.

关键词： stream cipher single cycle T-function linear complexity

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DLPlib： A Library for Deep Learning Processor

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Journal of computer Science & technology 2017年第2期32卷 286-296页

作者： Hui-Ying Lan Lin-Yang Wu Xiao Zhang Jin-Hua Tao Xun-Yu Chen Bing-Rui Wang Yu-Qing Wang Qi Guo Yun-Ji Chen State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Microprocessor Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Department of Computer Science University of Science and Technology of China Hefei 230026 China

Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework （e.g., TPU （tensor processing unit） is integrated into Tensorflow directly）. However, this will obstruct other frameworks to profit from the programming interface, The alternative approach is to design a framework-independent low-level library for deep learning processors （e.g., the deep learning library for GPU, cuDNN）. In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPIib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neur

关键词： deep learning processor API library DLPlib

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Effect of pre-processing methods on microarray-based SVM classifiers in affymetrix genechips

Effect of pre-processing methods on microarray-based SVM cla...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Florido, J.P. Pomares, H. Rojas, I. Urquiza, J.M. Herrera, L.J. Claros, M.G. Department of Computer Architecture and Computer Technology CITIC-UGR University of Granada Spain Department of Molecular Biology and Biochemistry University of Malaga Spain

ISBN: (纸本)9781424469178

Affymetrix High Oligonucleotide expression arrays are widely used for the high-throughput assessment of gene expression of thousands of genes simultaneously. Although disputed by several authors, there are non-biological variations and systematic biases that must be removed as much as possible through the pre-processing step before an absolute expression level for every gene is assessed. It is important to evaluate microarray pre-processing procedures not only to the detection of differentially expressed genes, but also to classification, since a major use of microarrays is the expression-based phenotype classification. Thus, in this paper, we use several cancer microarray datasets to assess the influence of five different pre-processing methods in Support Vector Machine-based classification methodologies with different kernels: linear, Radial Basis Functions (RBFs) and polynomial. © 2010 IEEE.

关键词： Microarrays

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