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Fast Subspace Clustering Based on the Kronecker Product

Fast Subspace Clustering Based on the Kronecker Product

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international conference on pattern recognition

作者： Lei Zhou Xiao Bai Liang Zhang Jun Zhou Edwin Hancock School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Jiangxi Research Institute Beihang University Beijing China School of Information and Communication Technology Griffith University Nathan Australia University of York York U.K.

Subspace clustering is a useful technique for many computer vision applications in which the intrinsic dimension of high-dimensional data is often smaller than the ambient dimension. Spectral clustering, as one of the main approaches to subspace clustering, often takes on a sparse representation or a low-rank representation to learn a block diagonal self-representation matrix for subspace generation. However, existing methods require solving a large scale convex optimization problem with a large set of data, with computational complexity reaches O(N³) for N data points. therefore, the efficiency and scalability of traditional spectral clustering methods can not be guaranteed for large scale datasets. In this paper, we propose a subspace clustering model based on the Kronecker product. Due to the property that the Kronecker product of a block diagonal matrix with any other matrix is still a block diagonal matrix, we can efficiently learn the representation matrix which is formed by the Kronecker product of k smaller matrices. By doing so, our model significantly reduces the computational complexity to O(kN³/^k). Furthermore, our model is general in nature, and can be adapted to different regularization based subspace clustering methods. Experimental results on two public datasets show that our model significantly improves the efficiency compared with several state-of-the-art methods. Moreover, we have conducted experiments on synthetic data to verify the scalability of our model for large scale datasets.

关键词： Adaptation models Computational modeling Scalability Clustering methods Face recognition Memory management Data models

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A New Revised Group DEMATEL method with application on facility location problem 10

A New Revised Group DEMATEL method with application on facil...

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10th international conference on Information Technology and Quantitative Management, ITQM 2023

作者： Radulescu, Constanta Zoie Radulescu, Marius Boncea, Radu National Institute for Research and Development in Informatics 8-10 Maresal Averescu Bucharest011455 Romania "Gheorghe Mihoc-Caius Iacob" Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Calea 13 Septembrie No.13 Bucharest050711 Romania

Multi-criteria methods are commonly used in facility location problem to evaluate different facility locations in the presence of a set of criteria in order to select the best facility location. the increasing availability of Internet-of-things (IoT) data, can be a help in gathering the necessary data for the location evaluation. the paper proposes a New Revised Group DEMATEL (NRG-DEMATEL) multi-criteria method, aiming to analyse cause-and-effect relationships among a set of criteria. this method provides general conditions which imply the convergence to the null matrix of the sequence of powers of the initial relation matrix, hence the total influence matrix can be computed. DEMATEL is infeasible when the sequence of powers of the initial relation matrix does not converge to the null matrix. the NRG-DEMATEL can be applicable to all situations feasible or infeasible. For the cases that are feasible, our method leads to the same result as the original method DEMATEL. the causality diagram and the digraph, that can visualize the causal relationships of a set of criteria, are built with the NRG-DEMATEL method. In order to reduce the complexity of the digraph, a threshold value is set to filter out negligible effects. Two methods for computing the thresholds are considered in this paper: the arithmetic mean method and the arithmetic mean - standard deviation method. An application of the NRG-DEMATEL to hospital facility problem is realized. © 2023 the Authors. Published by Elsevier B.V. this is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth international conference on Information Technology and Quantitative Management.

关键词： Directed graphs

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Fine Characterization of the Tidal-Controlled Delta Sedimentary System: Taking the Lower Part of the Cretaceous Tanopqin Formation of the ST Gas Field in the Western Siberian Basin as an Example 10th

Fine Characterization of the Tidal-Controlled Delta Sediment...

引用

10th international Field Exploration and Development conference, IFEDC 2020

作者： Chen, Ye-fei Li, Kong-chou Ni, Jun Wang, Yong-hua Research Institute of Petroleum Exploration and Development PetroChina Beijing China CNPC International Russia PetroChina Beijing China

ISBN: (纸本)9789811607622

Based on core, logging, and logging data, combined with modern sedimentary and seismic sedimentology studies, the tidal-controlled delta deposition system of the lower Cretaceous Tanopqin Formation in the ST gas field of the Western Siberian Basin was analyzed, and the distribution pattern of sedimentary facies was predicted to establish the ST the sedimentary model of the tidal-control delta in the gas field, and the model of sedimentary facies of the sedimentary system was established by the method of zoning and sub-zone facies modeling. the target layer develops typical tidal bedding sedimentary structures such as lens bedding and wave bedding. Vertically, the whole is anti-rhythmic, with multi-stage tidal sand dams in the lower part and branch channels in the upper part. On the plane, in the middle and eastern parts of the work area, there are mainly river channels and inter-channel sediments in the tidal-control delta plain. there are many river channels with bifurcations and mergers;in the central and western regions of the work area, they are mainly tidal-control delta front deposits, in the tidal-control delta inside the front edge, there are multiple underwater branch channels near the tidal-controlled delta plain. Numerous tidal estuary sand dams are developed in front of the branch channels. the rest of the tidal-controlled delta is mainly muddy sediments. In the modeling of tide-controlled delta facies, the modeling method is used to optimize, the zoning and zoning phase modeling method is adopted, the river-based area adopts the target-based method, the multi-point geological statistical method is used for the development area of the tidal sand dam, and the random simulation is used for the coastal area. the method has better reproduced the morphological characteristics of river channels and tidal dams, and the prediction effect is better. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rivers

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Variational Deep Embedding Clustering by Augmented Mutual Information Maximization

Variational Deep Embedding Clustering by Augmented Mutual In...

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international conference on pattern recognition

作者： Qiang Ji Yanfeng Sun Yongli Hu Baocai Yin Faculty of Information Technology Beijing University of Technology Beijing China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

Clustering is a crucial but challenging task in pattern analysis and machine learning. Recent many deep clustering methods combining representation learning with cluster techniques emerged. these deep clustering methods mainly focus on the correlation among samples and ignore the relationship between samples and their representations. In this paper, we propose a novel end-to-end clustering framework, namely variational deep embedding clustering by augmented mutual information maximization (VCAMI). From the perspective of VAE, we prove that minimizing reconstruction loss is equivalent to maximizing the mutual information of the input and its latent representation. this provides a theoretical guarantee for us to directly maximize the mutual information instead of minimizing reconstruction loss. therefore we proposed the augmented mutual information which highlights the uniqueness of the representations while discovering invariant information among similar samples. Extensive experiments on several challenging image datasets show that the VCAMI achieves good performance. we achieve state-of-the-art ACC results for clustering on MNIST (99.5%) and CIFAR-10 (65.4%) to the best of our knowledge.

关键词： Correlation Clustering methods Estimation Robustness Data mining Task analysis pattern analysis

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Measuring the small-signal response of diode rectifier loads using a DSP controlled switching converter system

Measuring the small-signal response of diode rectifier loads...

引用

international conference on Harmonics and Quality of Power

作者： H.D. Laird S.D. Round R.M. Duke Department of Electrical and Computer Engineering University Of Canterbury Christchurch New Zealand

ISBN: (纸本)0780376714

the assumption that nonlinear rectifier loads contribute only to the steady state of a power system is commonly made in the design and analysis of power conditioners such as the shunt active filter. this tacitly assumes that the nonlinear rectifier load is less sensitive than the AC system. this paper presents experimental measurements of the sensitivity of nonlinear rectifiers made by injecting a perturbing current into the point of coupling of the rectifier. the perturbing current is generated with a DSP controlled switching power converter typically used in shunt active filters. the DSP system also measures the change in the load current. Results are presented for both single-phase and three-phase rectifiers. these show that both these rectifiers are sensitive to the perturbing current, that the response is measurable with relatively unsophisticated hardware and that the response has a well defined pattern in the frequencies that occur.

关键词： Diodes Rectifiers Digital signal processing Control systems Switching converters Current measurement Active filters Steady-state Power system analysis computing Power system measurements

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Forecasting Tea Production in the Context of Bangladesh Utilizing Machine Learning

Forecasting Tea Production in the Context of Bangladesh Util...

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international conference on computing and Networking Technology (ICCNT)

作者： Abdullah Al Ryan Silvia Kh Shuvessa Shahriar Mamun Habiba Dewan Arpita Md. Sazzadur Ahamed Dept. of CSE Daffodil International University Dhaka Bangladesh

One of the most popular drinks, second only to water, is tea. Bangladesh ranks as the world’s 10th-largest manufacturer of tea. Tea has a big impact on poverty reduction, rural development, and nutrition security. Over the past ten years, Bangladesh has increased its tea supply. According to the BTB figures, over 96.51 million kg were produced in 2021, an increase of almost 54% from that of 2012. As tea is a profitable crop from Bangladesh’s perspective, tea yield prediction can play a significant role in increasing the production of tea. In this paper, tea yield has been forecast using various machine learning algorithms based on area-based tea production and their weather data from 1968 to 2021. Necessary data has been collected from BBS, BARC, and BMD government organizations. Eight climate factors have been used for the research. the data model has been evaluated by using eight classification and regression algorithms, with the Random Forest classifier showing the best accuracy of 97%. With this approach, tea production can be increased while reducing food threats and managing it for other nations.

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A Memory Access pattern-Based Program Profiling System for Dynamic Parallelism Prediction

A Memory Access Pattern-Based Program Profiling System for D...

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IEEE international conference on Trust, Security and Privacy in computing and Communications

作者： Zijun Han Guangzhi Qu Dona Burkard Kelvin Dobbins Comput. Sci. & Eng. Dept. Oakland Univ. Rochester MI USA Res. & Innovation Center Ford Motor Co. Dearbon MI USA

ISBN: (纸本)9781509032068

Parallel computing is the simultaneous use of multiple computer resources to solve a computational problem. In order to automatically execute a sequential program so that inherent parallelism could utilize the underlying multi-core platforms, program profiling is necessary to learn the control and dataflow dependency which is critical for predicting the parallelization feasibility and finding parallelism solutions. In literature, algorithms and tools have been designed for either dynamic or static program analysis in order to increase the accuracy and performance in discovering all aspects of the target program. However, memory and runtime overhead remain two challenge problems for program profiling. In this work, based on the PIN framework, we have designed and implemented a memory access pattern-based program profiling system for sequential program parallelization prediction. Validation results on seven SPEC 2006 benchmark programs show the effectiveness of proposed system on both memory usage and cpu time for target program dynamic profiling.

关键词： Parallel processing History Memory management Engines Runtime Pins Heuristic algorithms PARALLEL PROCESSING (COMPUTERS) Runtime PIN Store management Heuristic algorithms Engines Bone Nails analysis programme sequential program Synclitism parallelism object programs Memory Memory CPU time

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Analysis of the Effect pattern of Mixing Ratio and Age on the Conductivity of Concrete 10

Analysis of the Effect Pattern of Mixing Ratio and Age on th...

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10th international conference on Advances in Machinery, Material Science and Engineering Application, MMSE 2024

作者： Chi, Hongyou Zhang, Shenghang Tang, Lei Li, Jun Li, Po Pan, Wenming Guangdong GDH Pearl River Delta Water Supply Co. Ltd Guangzhou510000 China Nanjing Hydraulic Research Institute Nanjing210029 China

ISBN: (纸本)9781643685465

Concrete is the most widely used building material, and its electrical index test has received more attention in recent years. the samples of different mix proportions (water-cement ratios, sand rate, accelerator) were made and tested by impedance analysis. the results show that the impedance analysis method can eliminate the polarization effect and test the electrical properties more stably;With the increase of age, the relationship between electrical conductivity and water cement ratio gradually changed from positive correlation to negative correlation;the conductivity of the sample with accelerator was slightly higher than that without accelerator;the electrical conductivity of concrete is basically negatively correlated with the sand content. there is no order of magnitude difference in the electrical index of concrete in the concrete mix ratio, and the difference gradually decreases with the increase of concrete age. the experimental results can provide reference for electromagnetic detection work. © 2024 the Authors.

关键词： Cements

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2. Image computing for digital pathology

2. Image computing for digital pathology

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international conference on pattern recognition

作者： Shishir Shah Edgar Gabriel University of Houston University of Houston Houston TX US

Summary form only given. Pathologists and cancer biologists rely on tissue and cellular analysis to study cancer expression, genetic profiles, and cellular morphology to understand the underlying basis for a disease and to grade the level of disease progression. Conventional analysis of tissue histology and sample cytology includes the steps of examination of the stained tissue or cell smear under a microscope, scoring the expression relative to the most highly expressing (densely stained) area on a predefined scale for normal, cancer, stromal regions based on the morphology of the tissue, estimating the percentage area of cancer tissue relative of normal and stroma, and multiplying the score by the percentage area of cancer region and converting to another predefined scale for statistical analyses. Most of this analysis is done manually or with limited tools to aid the scoring process. Over the last 5 years, automated and semi- automated microscope slide scanners have become available in the marketplace. these scanners rely on sophisticated microscopes and allow for the digitization of the entire sample at varying magnifications. this has led to the emergence of digital pathology and a growing amount of image data. Each sample digitized is typically of the order of 2.7 GB to 10 GB in size depending on the magnification of the digitizing system with an image size of 30,000 ? 30,000 pixels or larger. Further, current software and methods for automated scoring of tissue is very limited. this has led to an increased interest in identifying novel solutions to automated histology and cytology analysis. In order to achieve high computational accuracy with reasonable turnaround times, novel approaches from the data and resource management perspective are also required to address handling of image sizes outlined above. Two developments in computer industry make the current generation of scientists more likely to solve the performance challenges associated with the large ima

关键词： Pathology Image analysis Cancer Parallel processing Microscopy Morphology Diseases Concurrent computing Clustering algorithms Image storage

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Predicting Diabetes using CNN for Various Activation Functions: A Comparative Study

Predicting Diabetes using CNN for Various Activation Functio...

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international conference on System Modeling & Advancement in Research Trends (SMART)

作者： Sofia Goel Sudhansh Sharma RC Tripathi Indira Gandhi National Open University New Delhi India Faculty of Engineering and Computing Sciences TMU Moradabad UP

ISBN: (纸本)9781665439718

Diabetes mellitus is a chronic disease that produces blood glucose abnormalities. this needs to be monitored at regular intervals. Many machine learning models made significant contribution in the prediction of diabetes. One such deep learning model is the convolution neural network. It is a multi-layered network architecture that comprises convolution, pooling, output layers, and activation functions. Activation functions are used to learn and approximate the relationships between various features in the model for final output. this research paper focus on comparing the performance of the CNN model using four non-linear activation functions; sigmoid, tanh, ReLU, ELU for blood glucose prediction. the model uses a simglucose UVA/Padova dataset of 30 patients for experimental analysis. Additionally, the model presents a three-class classification problem, where the patient is classified as euglycemic, hypoglycaemic, and hyperglycaemic. Statistical measures like recall, precision, F-score, and accuracy are used to assess the performance of CNNs employing various activation functions. the experimental results show that CNN gives the maximum accuracy of 97.3% when applied with the ELU activation function.

关键词： Deep learning Training Convolution Neural networks Predictive models Glucose Diabetes

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