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Improving Auction Mechanisms for Online Real-Time Bidding Advertising with a Two-stage Resale Model

IFAC-PapersOnLine 2017年第1期50卷 13575-13580页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Real Time Bidding (RTB), widely publicized as one of the most promising big-data-driven business models for online computational advertising, has the potential of effectively monetizing user clicks and impressions via two-stage auctions with resale. Demand side platforms (DSPs) play a key role as intermediators in this auction process. Typically, the first-stage auctions will be conducted separately in each DSP to determine one winning advertiser registered on it, and in the second-stage auction, each DSP submits a bid based on its winning advertiser's bid to the ad exchange platform (AdX). The highest-bid DSP wins the ad impression from AdX and resells it to its winning advertiser in pursuit of the intermediate fee. This two-stage resale auction is a critical component in maintaining the effectiveness and efficiency of RTB ecosystems. In this paper, we strive to identify and design potential improvements for this auction mechanism with the aim of enhancing the total revenue of both advertisers and DSPs. We also validated our proposed auction mechanisms using the computational experiment approach. The experimental results indicate that our proposed mechanisms can make both advertisers and DSPs better off. Our work represents the first step towards a new research area of optimal mechanism design for RTB auctions, and is expected to provide useful managerial insights in RTB market practice. © 2017

关键词： Sales Commerce Machine design Auction mechanisms Computational advertisings Computational experiment Critical component Demand side Effectiveness and efficiencies Optimal mechanism designs Real time

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An IVC-Based Nuclear Emergency Parallel Evacuation System

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2021年第4期8卷 844-855页

作者： Tan, Ke Yang, Linyao Liu, Xin Xu, Yancai Lin, Jiazhen Wang, Xiao Wang, Fei-Yue State Key Lab Nucl Power Safety Monitoring Techno Shenzhen 518108 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China

Nuclear emergency evacuation is challenging and dangerous, with time constraints, resource limitations, and radiation exposure risks. The development of the Internet of Things (IoT) and artificial intelligence enables us to build an intelligent evacuation system to help mitigate this problem a great deal. In this article, we design the nuclear emergency parallel evacuation system based on the artificial systems (A), computational experiments (C), and parallel execution (P) approach and intelligent vehicle collaborative systems (IVCs). In this system, the evacuation risks of different regions under various possible scenarios are simulated and evaluated in the artificial systems. With data adversarially generated from the artificial systems and collected from sensors all over the area, an optimization model is proposed to find the optimal evacuation plans for emergent evacuation scenarios in the computational experiments. Eventually, the most suitable running strategy of autonomous buses will be selected and carried out based on the parallel execution in accordance with the real scene. A case study is conducted, and results indicate that the system can serve as an efficient tool for future nuclear emergency evacuation planning.

关键词： Computational modeling Planning Optimization Roads Mathematical model Collaboration Power generation ACP intelligent vehicle collaborative system nuclear evacuation optimization parallel intelligence

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A Fast Orientation Estimation Approach of Natural Images

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2016年第11期46卷 1589-1597页

作者： Cao, Zhiqiang Liu, Xilong Gu, Nong Nahavandi, Saeid Xu, De Zhou, Chao Tan, Min Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Res Ctr Precis Sensing & Control Inst Automat Beijing 100190 Peoples R China Deakin Univ Ctr Intelligent Syst Res Geelong Vic 3217 Australia

This correspondence paper proposes a fast orientation estimation approach of natural images without the help of semantic information. Different from traditional low-level features, our low-level features are extracted inspired by the biological simple cells of the visual cortex. Two approximated receptive fields to mimic the biological cells are presented, and a local rotation operator is introduced to determine the optimal output and local orientation corresponding to an image position, which serve as the low-level feature employed in this paper. To generate the low-level features, a bisection method is applied to the first derivative of the model of receptive fields. Moreover, the feature screener is introduced to eliminate too much useless low-level features, which will speed up the processing time. After all the valuable low-level features are combined, the overall image orientation is estimated. The proposed approach possesses several features suitable for real-time applications. First, it avoids the tedious training procedure of some conventional methods. Second, no specific reference such as the horizon is assumed and no a priori knowledge of image is required. The proposed approach achieves a real-time orientation estimation of natural images using only low-level features with a satisfactory resolution. The effectiveness of our proposed approach is verified on real images with complex scenes and strong noises.

关键词： Biological simple cell differential field natural image orientation estimation

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An optimized modeling method based on BPEL4WS

An optimized modeling method based on BPEL4WS

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Liu, Sheng Xiong, Gang Fan, Dong Yao, Jianshi State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Science Beijing 100190 China Chinese People's Liberation Army Beijing 100094 China

ISBN: (纸本)9781457705731

As an efficient business process execution language which supports web services, BPEL4WS is widely supported by the academic and the industrial circles. According to the shortcomings such as number of computer terms, abstract model definition and the complex description of people activity, this paper presents easy-to-use BPEL4WS modeling method and tool which encapsulates computer terms and convert business models to BPEL4WS models directly. In comparison to the other modeling methods, our method cut down the number of modeling elements by more than 85 percent and save the modeling time by 80 percent and accelerate model running by more than 40 percent. Thus it is more appropriate for popularization. © 2011 IEEE.

关键词： Web services

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intelligent Line Segment Perception With Cortex-Like Mechanisms

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2015年第12期45卷 1522-1534页

作者： Liu, Xilong Cao, Zhiqiang Gu, Nong Nahavandi, Saeid Zhou, Chao Tan, Min Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat Res Ctr Precis Sensing & Control Beijing 100190 Peoples R China Deakin Univ Ctr Intelligent Syst Res Geelong Vic 3217 Australia

This paper proposes a novel general framework for line segment perception, which is motivated by a biological visual cortex, and requires no parameter tuning. In this framework, we design a model to approximate receptive fields of simple cells. More importantly, the structure of biological orientation columns is imitated by organizing artificial complex and hypercomplex cells with the same orientation into independent arrays. Besides, an interaction mechanism is implemented by a set of self-organization rules. Enlightened by the visual topological theory, the outputs of these artificial cells are integrated to generate line segments that can describe nonlocal structural information of images. Each line segment is evaluated quantitatively by its significance. The computation complexity is also analyzed. The proposed method is tested and compared to state-of-the-art algorithms on real images with complex scenes and strong noises. The experiments demonstrate that our method outperforms the existing methods in the balance between conciseness and completeness.

关键词： Artificial cells biological visual cortex line segment perception (LSP) self-organization

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Social Computing: From Crowdsourcing to Crowd Intelligence by Cyber Movement OrganizationsZ

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2019年第4期6卷 619-626页

作者： Wang, Fei-Yue Wang, Xiao Li, Juanjuan Ye, Peijun Li, Qiang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Shandong Peoples R China Res Ctr Sci & Technol Innovat Beijing 100190 Peoples R China

Welcome to the fourth issue of the IEEE Transactions on Computational Social systems (TCSS), which includes 16 regular papers and a brief discussion on social computing. We would also like to inform you that IEEE will conduct its regular 5-year review for TCSS at its TAB meeting in November at Boston. Any suggestions for our review report are welcome!

关键词： Crowdsourcing

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Efficient Calibration of Agent-Based Traffic Simulation Using Variational Auto-Encoder 25

Efficient Calibration of Agent-Based Traffic Simulation Usin...

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IEEE 25th International Conference on intelligent Transportation systems (ITSC)

作者： Ye, Peijun Zhu, Fenghua Lv, Yisheng Wang, Xiao Chen, Yuanyuan Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

In agent-based traffic simulation, calibration is an essential stage before the models applied to reproduce the individual/group travel behaviors. While traditional methods suffer from a high computational complexity, this paper proposes an improved method to alleviate the computational burden for large-scaled simulations. Specifically, we introduce variational auto-encoder to compress the original agent state vector into a lower dimensional hidden space, where the state transfer probability is calculated fast. Then the probability is mapped into the original space through a decoder, to achieve the agent travel parameters. The dynamic calibration method is tested with other baselines in urban travel demand analysis. Experiment results demonstrate that our method brings about 19% elevation of efficiency with the same accuracy of calibration.

关键词： Technological innovation Computational modeling Traffic control Probability Calibration Space exploration Decoding

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Vehicle License Plate Recognition Based on Class-specific ERs and SaE-ELM 17

Vehicle License Plate Recognition Based on Class-specific ER...

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IEEE 17th International Conference on intelligent Transportation systems (ITSC)

作者： Gou, Chao Wang, Kunfeng Li, Bo Wang, Fei-yue Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781479960781

In this paper, an effective approach to vehicle license plate recognition based on Extremal Regions (ERs) and Self-adaptive Evolutionary Extreme Learning Machine (SaE-ELM) is proposed. In the license plate detection step, some computations including morphological operations, various filters, different contours and validations are sequentially performed to extract some image regions as candidate license plates. Then, accurate character segmentation is achieved through a proper selection of ERs. In the character recognition step, the HOG (histogram of oriented gradients) feature vector in each character region is extracted, and then the characters are recognized using an offline trained pattern classifier of SaE-ELM. Experimental results show that our approach works quite well in complex traffic environments.

关键词： Learning systems

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A Building Evacuation Model Integrated with Multiple Algorithms

A Building Evacuation Model Integrated with Multiple Algorit...

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Chinese Automation Congress (CAC)

作者： Zhao, Xiaoyu Liu, Xiwei Gong, Xiaoyan Jing, Sifeng Lie, Jian Beijing Univ Technol Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Qingdao Acad Intelligent IndInst Smart Educ Syst Beijing Peoples R China Beijing Univ Technol Beijing Peoples R China

ISBN: (纸本)9781728140940

Due to the increasing frequency of terrorist attacks all over the world, we designed an emergency evacuation model under the situation of the terrorist attacks. This model uses the Ant Colony Optimization (ACO) as a macro solution, the Cellular Automata (CA) as a micro-control method, and the Queuing Theory Model (QTM) to solve the queuing problem of escape exits. Based on the model we built, the optimized evacuation plan under different conditions were obtained.

关键词： evacuation queuing theory model improved cellular automaton ant colony optimization

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Visual Vehicle Tracking Based on Conditional Random Fields 17

Visual Vehicle Tracking Based on Conditional Random Fields

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IEEE 17th International Conference on intelligent Transportation systems (ITSC)

作者： Liu, Yuqiang Wang, Kunfeng Wang, Fei-Yue Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China

ISBN: (纸本)9781479960781

This paper proposes an approach to moving vehicle tracking in surveillance videos based on conditional random fields (CRF). The key idea is to integrate a variety of relevant knowledge about vehicle tracking into a uniform probabilistic framework by using the CRF model. In this work, the CRF model integrates spatial and temporal contextual information of vehicle motion, and the appearance information of the vehicle. An approximate inference algorithm, loopy belief propagation, is used to recursively estimate the vehicle region from the history of observed images. Moreover, the background model is updated adaptively to cope with non-stationary background processes. Experimental results show that the proposed approach is able to accurately track moving vehicles in monocular image sequences. Besides, region-level tracking realizes precise localization of vehicles.

关键词： Vehicle tracking conditional random fields region-level tracking

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