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International Conference on Life System Modeling and Simulation / International Conference on Intelligent Computing for Sustainable Energy and Environment (LSMS-ICSEE)

作者： Wang, Ling Fu, Xiping Menhas, Muhammad Ilyas Fei, Minrui Shanghai Univ Sch Mechatron & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China

ISBN: (纸本)9783642155963

Differential evolution (DE) is a simple, yet efficient global optimization algorithm. As the standard DE and most of its variants operate in the continuous space, this paper presents a modified binary differential evolution algorithm (MBDE) to tackle the binary-coded optimization problems. A novel probability estimation operator inspired by the concept of distribution of estimation algorithm is developed, which enables MBDE to manipulate binary-valued solutions directly and provides better tradeoff between exploration and exploitation cooperated with the other operators of DE. The effectiveness and efficiency of MBDE is verified in application to numerical optimization problems. The experimental results demonstrate that MBDE outperforms the discrete binary DE, the discrete binary particle swarm optimization and the binary ant system in terms of both accuracy and convergence speed on the suite of benchmark functions.

关键词： Differential Evolution binary encoding Probability Estimation Operator Multidimensional Knapsack Problem

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Sparse Representation Based Image Super-resolution Using Large Patches

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Chinese Journal of Electronics 2018年第4期27卷 813-820页

作者： LIU Ning ZHOU Pan LIU Wenju KE Dengfeng National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Department of Electrical and Computer Engineering National University of Singapore

This paper addresses the problem of generating a high-resolution image from a low-resolution image. Many dictionary based methods have been proposed and have achieved great success in super resolution application. Most of these methods use small patches as dictionary atoms, and utilize a unified dictionary pair to conduct reconstruction for each patch, which may limit the super resolution performance. We use large patches instead of small ones to combine a dictionary and to conduct patch reconstruction. Since a large patch contains more meaningful information than a small one, the reconstruction result may have more high frequency details. To guarantee the completeness of the dictionary with large patch, the scale of the dictionary should be large as well. To handle the storage and calculation problems with large dictionaries,we adopt a binary encoding method. This method can preserve local information of patches. For each patch in the low-resolution image, we search its similar patches in the low-resolution dictionary to obtain a sub-dictionary. We compute its sparse representation to get the corresponding high-resolution version. Global reconstruction constraint is enforced to eliminate the discrepancy between the SR result and the ground truth. Experimental results demonstrate that our method outperforms other super resolution methods, especially when the magnification factor is large or the image is blurred by white Gaussian noise.

关键词： Super resolution Sparse representations binary encoding

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Systematic prediction of yield-line configurations for arbitrary polygonal plates

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ENGINEERING STRUCTURES 2008年第7期30卷 2081-2093页

作者： Wuest, Jochen Wagner, Werner Univ Karlsruhe TH Inst Baustat D-76131 Karlsruhe Germany Ingenieurgrp Bauen D-76135 Karlsruhe Germany

In addition to the well-established finite element method in recent years several optimization approaches have been developed concerning the yield-line theory. This paper presents a new systematical algorithm to predict initial yield-line configurations of arbitrary polygonal plates. It contributes a solution to the task of detecting yield-line patterns in advance of an optimization process. For this reason a ciphering of yield-line patterns is proposed and a new application of Catalan numbers and binary trees is demonstrated. After a subsequent refining a triangular element is used in combination with a simplex optimization procedure in order to determine the ultimate load of the considered yield-line configuration. Moreover, further optimization strategies like the direct search method and the conjugate gradient method lead to the final solution of the problem. The use and the efficiency of the new approach are demonstrated with three examples. (c) 2008 Elsevier Ltd. All rights reserved.

关键词： yield-line theory yield-line prediction algorithm yield-line optimization polygonal plate structures application of catalan numbers binary encoding limit load determination

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UbiSitePred: A novel method for improving the accuracy of ubiquitination sites prediction by using LASSO to select the optimal Chou's pseudo components

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2019年 184卷 28-43页

作者： Cui, Xiaowen Yu, Zhaomin Yu, Bin Wang, Minghui Tian, Baoguang Ma, Qin Qingdao Univ Sci & Technol Coll Math & Phys Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Artificial Intelligence & Biomed Big Data Res Ctr Qingdao 266061 Peoples R China Univ Sci & Technol China Sch Life Sci Hefei 230027 Anhui Peoples R China Univ Calgary Dept Biochem & Mol Biol Med Genet & Oncol Calgary AB T2N 4N1 Canada Ohio State Univ Coll Med Dept Biomed Informat Columbus OH 43210 USA

Ubiquitination is an essential process in protein post-translational modification, which plays a crucial role in cell life activities, such as proteasomal degradation, transcriptional regulation, and DNA damage repair. Therefore, recognition of ubiquitination sites is a crucial step to understand the molecular mechanisms of ubiquitination. However, the experimental verification of numerous ubiquitination sites is time-consuming and costly. To alleviate these issues, a computational approach is needed to predict ubiquitination sites. This paper proposes a new method called UbiSitePred for predicting ubiquitination sites combined least absolute shrinkage and selection operator (LASSO) feature selection and support vector machine. First, we use binary encoding (BE), pseudo-amino acid composition (PseAAC), the composition of k-spaced amino acid pairs (CKSAAP), position-specific propensity matrices (PSPM) to extract the sequence feature information;thus, the initial feature space is obtained. Secondly, LASSO is applied to remove the feature redundancy information and selects the optimal feature subset. Finally, the optimal feature subset is input into the support vector machine (SVM) to predict the ubiquitination sites. Five-fold cross-validation shows that UbiSitePred model can achieve a better prediction performance compared with other methods, the AUC values for Set1, Set2, and Set3 are 0.9998, 0.8887, and 0.8481, respectively. Notably, the UbiSitePred has overall accuracy rates of 98.33%, 81.12%, and 76.90%, respectively. The results demonstrate that the proposed method is significantly superior to other state-of-the-art prediction methods and provide a new idea for the prediction of other post-translational modification sites of proteins. The source code and all datasets are available at https://***/QUST-AIBBDRC/UbiSitePred/.

关键词： Ubiquitination sites binary encoding Pseudo-amino acid composition Composition of k-spaced amino acid pairs Position-specific propensity matrices Least absolute shrinkage and selection operator

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Multitemporal image encoding for monitoring spatiotemporal variations of water bodies using Landsat 8 Operational Land Imager (OLI) data

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JOURNAL OF APPLIED REMOTE SENSING 2020年第3期14卷

作者： Jijon-Palma, Mario Ernesto Amisse, Caisse Silva Centeno, Jorge Antonio Univ Fed Parana Geomat Dept Postgrad Program Geodes Sci Earth Sci Sect Curitiba Parana Brazil

Remote sensing enables multitemporal information of the Earth's surface and the dynamic processes that affect the environment. Given the considerable data availability, methods to summarize multitemporal datasets are needed to support the analysis. Our study introduces and compares methods to monitor temporal variations of water bodies based on multitemporal image composition. For this purpose, the presence of water at different dates is mapped applying the normalized difference water index using two encoding methods. The first one is based on the cumulative analysis of water in the pixel along time, and the second one uses the principle of binary encoding. The cumulative analysis helps to visualize more humid and dry areas, while binary encoding indicates the monthly variations of the lake surface, storing information about the dynamics of the phenomenon. The methods are compared using Landsat time series of Lake Poopo obtained between 2013 and 2019. The results showed that binary encoding allows detecting when and where severe droughts affect the water body and its recovery. In addition, it was possible to monitor the severe drought that affected the lake in 2016 and it was also noticed that its surface is still below the level registered before the drought in 2013. (C) 2020 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： binary encoding Lake Poopo water bodies drought dry season

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Sparse representation based image super-resolution on the KNN based dictionaries

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OPTICS AND LASER TECHNOLOGY 2019年 110卷 135-144页

作者： Liu, Ning Xu, Xing Li, Yujie Zhu, Anna Univ Elect Sci & Technol China Chinese Acad Sci Natl Lab Pattern Recognit Sch Comp Sci & Engn Chengdu Sichuan Peoples R China Univ Elect Sci & Technol China Ctr Future Media Chengdu Sichuan Peoples R China Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Sichuan Peoples R China Yangzhou Univ Yangzhou Jiangsu Peoples R China Wuhan Univ Technol Wuhan Hubei Peoples R China

This paper addresses the problem of single image super-resolution (SR). In recent years, sparse representation based SR methods have been proposed and achieved great success. Traditional sparse representation based SR methods learn a unified high-resolution (HR) and low-resolution (LR) dictionary pair. All LR patches share the same dictionary pair to conduct reconstruction to get their corresponding HR patches. The reconstruction process introduces reconstruction error, which limits the performance of SR results. In this paper, to minimize the reconstruction error, we utilize a K-Nearest-Neighbours (KNN) based dictionary pair for each LR patch instead of the unified dictionary pair to conduct the reconstruction process. The KNN based dictionaries are selected among a huge dictionary which contains hundreds of millions of patch pairs. To speed up the KNN retrieval process, we adopt a binary encoding method which preserves local information for the LR patches, and retrieve the KNN of each LR patch in the Hamming space. Besides, since a large patch contains more structured information than a small patch, we utilize large patches instead of small ones as the atoms of dictionaries, which further improves the SR results. Experimental results demonstrate that our method outperforms the existed state-of-the-art methods, especially when the magnification factor is large or the image is blurred. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Super resolution Sparse representations K-Nearest-Neighbours binary encoding

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Dynamic programming on the word RAM

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ALGORITHMICA 2003年第2期35卷 128-145页

作者： Pisinger, D Univ Copenhagen DIKU DK-2100 Copenhagen Denmark

Dynamic programming is one of the fundamental techniques for solving optimization problems. In this paper we propose a general framework which can be used to decrease the time and space complexity of these algorithms with a logarithmic factor. The framework is based on word encoding, i.e. by representing subsolutions as bits in an integer. In this way word parallelism can be used in the evaluation of the dynamic programming recursion. Using this encoding the subset-sum problem can be solved in O(nb/log b) time and O(b/log b) space, where n is the number of integers given and b is the target sum. The knapsack problem can be solved in O(nm/log m) time and O(m/log m) space, where n is the number of items and m = max{b, z} is the maximum of the capacity b and the optimal solution value z. The problem of finding a path of a given length b in a directed acyclic graph G = (V, E) can be solved in O(\E\ b/log b) time and O(\V\ b/log b) space. Several other examples are given showing the generality of the achieved technique. Extensive computational experiments are provided to demonstrate that the achieved results are not only of theoretical interest but actually lead to algorithms which are up to two orders of magnitude faster than their predecessors. This is a surprising observation as the increase in speed is larger than the word size of the processor.

关键词： dynamic programming binary encoding knapsack problem word RAM

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Application of the Matched Filtering Method to Study the Stream Sediment Geochemistry and Prospecting Prediction of the Baiyun Gold Deposit, Qingchengzi Ore Field, China

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MINING METALLURGY & EXPLORATION 2024年第1期41卷 379-394页

作者： Chen, Jiang Yang, Fengchao Bedini, Enton Chen, Xiaoyan Zhang, Chunhui Dong, Hang Res Ctr Appl Geol China Geol Survey Chengdu 610031 Peoples R China China Geol Survey Shenyang Geol Survey Ctr Shenyang 110034 Peoples R China Geol Survey Denmark & Greenland GEUS Oster Voldgade DK-101350 Copenhagen Denmark Jilin Univ Coll Geoexplorat Sci & Technol Changchun 130026 Peoples R China

The alteration formed by the reaction of ore-bearing fluid and wall rock is often used as an important prospecting indicator, resulting in the dilution or enrichment of metals or related trace elements. A variety of rock-forming and metallogenic elements have been analyzed in regional stream sediments so that the relationship between the ore-bearing altered rock and the change in the geochemical elemental content can be obtained. Therefore, by using appropriate models, such as matched filtering, the abundance of the distribution of wall rock alteration, similar to the discovered deposits, can be modeled by using the distribution of geochemical elements in the region, and the areas with high distribution abundances are usually favorable prospecting targets. The alteration types related to gold mineralization in the Baiyun gold deposit are potassium feldspar alteration, silicification, pyritization, sericitization, and chloritization. In this paper, the geochemical data of the Qingchengzi ore field (1:200,000 and 1:50,000) have been used to form geochemical images through rasterization. In the three sections of the Baiyun gold deposit, binary-coded curves have been formed, revealing the differences in geochemical elements in stream sediments between altered rocks and the rocks surrounding the Baiyun gold mine. Among them, Au, W, and Mo are enriched elements, while Sn, Zn, and Hg are depleted elements. Several gold deposits are found in the predicted altered rock area by using the matched filtering method during fieldwork, which shows the effectiveness of the method.

关键词： Matched filtering Hydrothermal alteration Baiyun gold deposit binary encoding Enrichment and depletion

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Convergence Analysis of Distributed Set-Valued Information Systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2016年第6期61卷 1477-1491页

作者： Fagiolini, Adriano Dubbini, Nevio Martini, Simone Bicchi, Antonio Univ Pisa Interdept Res Ctr E Piaggio Fac Engn I-56126 Palermo Italy Univ Palermo Dept Energy Informat Engn & Math Models I-90138 Palermo Italy Ist Italiano Tecnol Dept Adv Robot I-16163 Genoa Italy

This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not represented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the network is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distributed geographic information system, leading to successful information reconstruction from partial and corrupted data, is used to illustrate the applications of the proposed methods.

关键词： binary encoding boolean dynamic systems consensus algorithms convergence cooperative systems distributed information systems set-valued dynamic maps

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Classifying and querying very large taxonomies with bit-vector encoding

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JOURNAL OF INTELLIGENT INFORMATION SYSTEMS 2017年第1期48卷 1-25页

作者： Ait-Kaci, Hassan Amir, Samir Univ Claude Bernard Lyon 1 Dept Informat LIRIS Villeurbanne France

In this article, we address the question of how efficiently Semantic Web (SW) reasoners perform in processing (classifying and querying) taxonomies of enormous size and whether it is possible to improve on existing implementations. We use a bit-vector encoding technique to implement taxonomic concept classification and Boolean-query answering. We describe the technique we have used, which achieves high performance, and discuss implementation issues. We compare the performance of our implementation with those of the best existing SW reasoning systems over several very large taxonomies under the exact same conditions for so-called TBox reasoning. The results show that our system is among the best for concept classification and several orders-of-magnitude more efficient in terms of response time for query answering. We present these results in detail and comment them. We also discuss pragmatic issues such as cycle detection and decoding.

关键词： binary encoding Taxonomic reasoning Query optimization Semantic web

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