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2017 2nd International Conference on Software, Multimedia and Communication Engineering（SMCE 2017)

作者： Jun-yan ZHANG Chen-hui YANG Hai-ying WANG College of Information Science and Engineering Chengdu UniversityChengdu 610106China Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan Chengdu University

DNA Sequence Alignment is one of the most basic and most important operations in *** this paper,we put forward to SDk S algorithm based on k-tuple statistic,which is a kind of probability *** positive transition probability matrix,the negative transition probability matrix,and the logarithmic ration are computed based on Markov *** obtaining converting sequence,we get the results of k-tuple ***,the similarity measurement can be gained according to above *** the minimum support is given,we can identify two DNA sequences is similarity or *** experimental results show that SDk S algorithm has better effective performance in saving computing time.

关键词： Sequence alignment k-tuple statistic Markov model Similarity measurement

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Dynamic round robin scheduling algorithm for μc/OS-III

Boletin Tecnico/Technical Bulletin

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Boletin Tecnico/Technical Bulletin 2017年第7期55卷 8-15页

作者： Zhang, Chunhong Ren, Jianqiang Luo, Ping College of Mathematics and Information Langfang Teachers University Langfang Hebei065000 China Institute of Pattern Recognition and Intelligent System Langfang Teachers University Langfang Hebei065000 China Langfang Key Laboratory of Intelligent Transportation System Langfang Hebei065000 China

In μC/OS-III, the traditional round robin algorithm is inefficient for tasks with the same priority. To solve this problem, this paper proposes a dynamic round robin scheduling algorithm based on the shortest remaining time first, called SRTFDRR. The algorithm determines the scheduling order according to the submission time and the remaining execution time of each task;For tasks with the same priority, set up multiple ready queues, each queue calculates the time slice independently based on the average value of the remaining execution time of the task;The ready task is inserted into the ready queue RQ1 of the corresponding priority in the order of burst time increments;If the priority of the queue task is the current highest priority, the SRTFDRR algorithm runs the task in the queue RQ1;If the time slice expires, there is a task in RQ1 that has not yet finished, and the remaining execution part moves into queue RQ2 waiting for scheduling again, and so on until all tasks are finished. A multi-level queue is formed during the scheduling process. Simulation results show that, compared with the traditional RR algorithm, the SRTFDRR algorithm reduces the average turnaround time, average waiting time, average response time and switching times. It performs well in performance, overhead, and fairness of scheduling.

关键词： Scheduling

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Sea: A combined model for heat demand prediction

arXiv

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arXiv 2018年

作者： Xie, Jiyang Guo, Jiaxin Ma, Zhanyu Xue, Jing-Hao Sun, Qie Li, Hailong Guo, Jun Pattern Recognition and Intelligent Systems Lab Beijing University of Posts and Telecommunications Beijing100876 China Department of Statistical Science University College London London United Kingdom Institute of Thermal Science and Technology Shandong University Jinan250100 China School of Business Society and Engineering Mälardalen University Västerås Sweden Tianjin Key Laboratory of Refrigeration Technology School of Mechanical Engineering Tianjin University of Commerce Tianjin300134 China

Heat demand prediction is a prominent research topic in the area of intelligent energy networks. It has been well recognized that periodicity is one of the important characteristics of heat demand. Seasonal-trend decomposition based on LOESS (STL) algorithm can analyze the periodicity of a heat demand series, and decompose the series into seasonal and trend components. Then, predicting the seasonal and trend components respectively, and combining their predictions together as the heat demand prediction is a possible way to predict heat demand. In this paper, STL-ENN-ARIMA (SEA), a combined model, was proposed based on the combination of the Elman neural network (ENN) and the autoregressive integrated moving average (ARIMA) model, which are commonly applied to heat demand prediction. ENN and ARIMA are used to predict seasonal and trend components, respectively. Experimental results demonstrate that the proposed SEA model has a promising performance. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Who will win practical artificial intelligence? AI engineerings in China

arXiv

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arXiv 2017年

作者： Wu, Huai-Yu Wang, Feiyue Pan, Chunhong National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Currently, Artificial Intelligence (AI) has won unprecedented attention and is becoming the increasingly popular focus in China. This change can be judged by the impressive record of academic publications, the amount of state-level investment and the presence of nationwide participation and devotion. In this paper, we place emphasis on discussing the progress of artificial intelligence engineerings in China. We first introduce the focus on AI in Chinese academia, including the supercomputing brain system, Cambrian Period supercomputer of neural networks, and biometric systems. Then, the development of AI in industrial circles and the latest layout of AI products in companies, such as Baidu, Tencent, and Alibaba, are introduced. Last, we bring in the opinions and arguments of the main intelligentsia of China about the future development of AI, including how to examine the relationship between humanity on one side and science and technology on the other. Copyright © 2017, The Authors. All rights reserved.

关键词： Artificial intelligence

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Cross-media analysis and reasoning: advances and directions

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Frontiers of Information Technology & Electronic Engineering 2017年第1期18卷 44-57页

作者： Yu-xin PENG Wen-wu ZHU Yao ZHAO Chang-sheng XU Qing-ming HUANG Han-qing LU Qing-hua ZHENG Tie-jun HUANG Wen GAO Institute of Computer Science and Technology Peking University Department of Computer Science and Technology Tsinghua University Institute of Information Science Beijing Jiaotong University National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Department of Computer Science and Technology Xi'an Jiaotong University School of Electronics Engineering and Computer Science Peking University

Cross-media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence. However, to the best of our knowledge, no existing work has summarized the state-of-the-art methods for cross-media analysis and reasoning or presented advances, challenges, and future directions for the field. To address these issues, we provide an overview as follows：（1） theory and model for cross-media uniform representation; （2） cross-media correlation understanding and deep mining; （3） cross-media knowledge graph construction and learning methodologies; （4） cross-media knowledge evolution and reasoning; （5） cross-media description and generation; （6） cross-media intelligent engines; and （7） cross-media intelligent applications. By presenting approaches, advances, and future directions in cross-media analysis and reasoning, our goal is not only to draw more attention to the state-of-the-art advances in the field, but also to provide technical insights by discussing the challenges and research directions in these areas.

关键词： Cross-media analysis Cross-media reasoning Cross-media applications

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Analysis of key Factors in Heat Demand Prediction with Neural Networks

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Energy Procedia 2017年 105卷 2965-2970页

作者： Jiyang Xie Hailong Li Zhanyu Ma Qie Sun Fredrik Wallin Zhongwei Si Jun Guo Pattern Recognition and Intelligent Systems Lab. Beijing University of Posts and Telecommunications China School of Business Society and Engineering Mälardalen University Sweden Institute of Thermal Science and Technology Shandong University China Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications China

The development of heat metering has promoted the development of statistic models for the prediction of heat demand, due to the large amount of available data, or big data. Weather data have been commonly used as input in such statistic models. In order to understand the impacts of direct solar radiance and wind speed on the model performance comprehensively, a model based on Elman neural networks (ENN) was adopted, of which the results can help heat producers to optimize their production and thus mitigate costs. Compared with the measured heat demand, the introduction of wind speed and direct solar radiation has opposite impacts on the performance of ENN and the inclusion of wind speed can improve the prediction accuracy of ENN. However, ENN cannot benefit from the introduction of both wind speed and direct solar radiation simultaneously.

关键词： District heating data processing prediction heat demand CHP plant

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Fast KNN search for big data with set compression tree and best bin first 2

Fast KNN search for big data with set compression tree and b...

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2nd International Conference on Cloud Computing and Internet of Things, CCIOT 2016

作者： Chen, Zhenjie Yan, Jingqi Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of Ministry of Education for System Control and Information Processing China Shanghai China

ISBN: (纸本)9781467398213

This paper proposes k nearest neighbors (kNN) search based on set compression tree (SCT) and best bin first (BBF) to deal with the problem for big data. The large compression rate by set compression tree is achieved by compressing the set of descriptors jointly instead of compressing on a per-descript or basis. So set compression tree has a good performance in kNN search at a low bit rate. At the same time, the best bin first (BBF) is a very efficient algorithm to find the approximately kNN from a large number of high dimensional feature descriptors. SCT-BBF is a novel exploration and it improves search performance in three aspects: First, SCT-BBF requires less memory footprint, which is important in big data age. Second, it increases accuracy compared traditional method like KD-Tree and original SCT. SCT-BBF can be used with other data processing methods like PCA and SIFT to perform better. Third, this paper adopts finer search to increase accuracy at a slight loss of speed. And it can extend to big data easily. © 2016 IEEE.

关键词： Big data

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Nonconvex penalties with analytical solutions for one-bit compressive sensing

arXiv

引用

arXiv 2017年

作者： Huang, Xiaolin Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai200240 China Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University East LansingMI48824 United States

One-bit measurements widely exist in the real world and can be used to recover sparse signals. This task is known as one-bit compressive sensing (1bit-CS). In this paper, we propose novel algorithms based on both convex and nonconvex sparsity-inducing penalties for robust 1bit-CS. We consider the dual problem, which has only one variable and provides a sufficient condition to verify whether a solution is globally optimal or not. For positive homogeneous penalties, a globally optimal solution can be obtained in two steps: a proximal operator and a normalization step. For other penalties, we solve the dual problem, and it needs to evaluate the proximal operators for many times. Then we provide fast algorithms for finding analytical solutions for three penalties: minimax concave penalty (MCP), 0norm, and sorted 1penalty. Specifically, our algorithm is more than 200 times faster than the existing algorithm for MCP. Its efficiency is comparable to the algorithm for the 1penalty in time, while its performance is much better than 1. Among these penalties, sorted 1is most robust to noise in different settings. Copyright © 2017, The Authors. All rights reserved.

关键词： Compressed sensing

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Correction to: Internet gaming disorder: deficits in functional and structural connectivity in the ventral tegmental area-Accumbens pathway

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Brain imaging and behavior 2019年第4期13卷 1182页

作者： Ruonan Wang Min Li Meng Zhao Dahua Yu Yu Hu Corinde E Wiers Gene-Jack Wang Nora D Volkow Kai Yuan School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. National Institute on Drug Abuse National Institutes of Health Bethesda MD 20892 USA. School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. kyuan@***. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. kyuan@***. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. kyuan@***. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. kyuan@***. Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University Guilin People's Republic of China. kyuan@***.

The original version of this article contained mistakes, and the authors would like to correct them. The correct details are given below.

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Oscillation resolution for massive cell phone traffic data 1

Oscillation resolution for massive cell phone traffic data

引用

1st Workshop on Mobile Data, MobiData 2016, co-located with MobiSys 2016

作者： Qi, Ling Qiao, Yuanyuan Abdesslem, Fehmi Ben Ma, Zhanyu Yang, Jie Center for Data Science Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Network BUPT Beijing China Decisions Networks and Analytics Laboratory SICS Stockholm Sweden Center for Data Science Pattern Recognition and Intelligent System Lab BUPT Beijing China

ISBN: (纸本)9781450343275

Cellular towers capture logs of mobile subscribers whenever their devices connect to the network. When the logs show data traffic at a cell tower generated by a device, it reveals that this device is close to the tower. The logs can then be used to trace the locations of mobile subscribers for different applications, such as studying customer behaviour, improving location-based services, or helping urban planning. However, the logs often suffer from an oscillation phenomenon. Oscillations may happen when a device, even when not moving, does not only connect to the nearest cell tower, but is instead unpredictably switching between multiple cell towers because of random noise, load balancing, or simply dynamic changes in signal strength. Detecting and removing oscillations are a challenge when analyzing location data collected from the cellular network. In this paper, we propose an algorithm called SOL (Stable, Oscillation, Leap periods) aimed at discovering and reducing oscillations in the collected logs. We apply our algorithm on real datasets which contain about 18.9 TB of traffic logs generated by more than 3 million mobile subscribers covering about 21000 cell towers and collected during 27 days from both GSM and UMTS networks in northern China. Experimental results demonstrate the ability and effectiveness of SOL to reduce oscillations in cellular network logs. © 2016 ACM.

关键词： Location based services

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