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检索条件"任意字段=Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition"

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2019 8th international conference on Affective computing and Intelligent Interaction, ACII 2019

2019 8th International Conference on Affective Computing and...

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8th international conference on Affective computing and Intelligent Interaction, ACII 2019

ISBN: (纸本)9781728138886

the proceedings contain 108 papers. the topics discussed include: altering body perception and emotion in physically inactive people through movement sonification;towards understanding emotional intelligence for behavior change chatbots;PAGAN: video affect annotation made easy;multiple metaphors in metaphoric gesturing;supporting mood introspection from digital footprints;the likeability-success tradeoff: results of the 2nd annual human-agent automated negotiating agents competition;you’ll be great: virtual agent-based cognitive restructuring to reduce public speaking anxiety;slices of attention in asynchronous video job interviews;visual cues for disrespectful conversation analysis;and development of an active sensing system for distress detection using skin conductance response.

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House Rent Prediction Based on Joint Model 19

House Rent Prediction Based on Joint Model

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proceedings of the 2019 8th international conference on computing and pattern recognition

作者： Kun Zhang LingCong Shen Ningning Liu School of Information Technology and Management University of International Business and Economics

ISBN: (纸本)9781450376570

With the development of the house leasing market, the house rents of several large cities in China have experienced rapid growth due to the increasing demand. In this paper, we focus on investigating various machine learning approaches to predict the house rent. Firstly, we not only have investigated different rent-related features including community condition, location, traffic and house condition, but also have employed various prediction models including XGBoost, LightGBM and CatBoost algorithms. Based on these, we proposed a joint model, which is a combination of above three models by linear weighting learned from least square method. Our best model ranks in top3% in the public Data Castle competition, which proves the joint model can effectively improve the accuracy and stability of the rent prediction compared to other prediction models.

关键词： CatBoost House Rent LightGBM Joint Model Prediction XGBoost

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House rent prediction based on joint model 8

House rent prediction based on joint model

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8th international conference on computing and pattern recognition, ICCPR 2019

作者： Zhang, Kun Shen, Ling Cong Liu, Ningning School of Information Technology and Management University of International Business and Economics China

ISBN: (纸本)9781450376570

关键词： Forecasting

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Evaluating the Performances of Electric Waveforms Analysis Relying on the Stationary Wavelet Transform 8

Evaluating the Performances of Electric Waveforms Analysis R...

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8th international conference on Modern Power Systems (MPS)

作者： Nicolae, Beam Diana Nicolae, Petre Marian Marinescu, Cristina Maria Marinescu, Radu Florin Univ Craiova Dept Comp Sci & Informat Technol Craiova Romania Univ Craiova Dept Elect Engn Aeronaut & Energet Craiova Romania

ISBN: (纸本)9781728107509

the extraction from distorted electric waveforms of the instantaneous components oscillating at the fundamental frequency must be characterized by accuracy and efficiency related to computational resources (memory and runtime). When the Stationary Wavelet Transform (SWT) is employed, these performances are affected by the sampling rate of the data acquisition system used to acquire the waveforms, the topology of the decomposition tree (number of components in the root nodes and number of levels) and the wavelet mother. this paper is dedicated to an original methodology conceived to deduce the optimal parameters required to provide an accurate and efficient operational context for the analysis relying on SWT. the studies are focused on three data acquisition systems characterized by different sampling rates, used by authors. A systematic procedure dedicated to parameters deducing is presented and validated on simulated and experimental signals. Comparative studies are provided as well.

关键词： power engineering computing power quality stationary wavelet transform

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proceedings for the 8th international conference on Modeling and Simulation of Metallurgical Processes in Steelmaking, STEELSIM 2019

Proceedings for the 8th International Conference on Modeling...

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8th international conference on Modeling and Simulation of Metallurgical Processes in Steelmaking, STEELSIM 2019

ISBN: (纸本)9781935117827

the proceedings contain 79 papers. the topics discussed include: technical limitations for developing a practicable LMF desulfurization model;prediction of mass transfer in hot metal reactors;analysis of transport and removal of inclusions in an industrial gas-stirred ladle;effect of an angled runner on the fluid flow pattern in the ingot casting process;numerical simulation of temperature and stress distributions inside the furnace tuyere;effects of lance configuration on the flow and combustion behavior of a pulverized coal plume in the tuyere;simulation and experiment studies on radial porosity distribution (RPD) of coke layer in blast furnace throat;and development and application of mathematical models to simulate liquid phase accumulation, drainage and heat transfer in blast furnace hearth.

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Error Rate Analysis of State-of-the-Art Algorithms for Face Detection 6

Error Rate Analysis of State-of-the-Art Algorithms for Face ...

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6th international conference on computing for Sustainable Global Development (INDIACom)

作者： Danish, Mohammad Chaurasia, Sumit Jain, Aarti AIACTR Dept ECE Delhi India

ISBN: (纸本)9789380544342

Face recognition is an easy task for humans but it is tedious and complex for computers. Currently, Eigenfaces, Local Binary pattern Histograms (LBPH) and Fisherfaces algorithms are considered as state-of-the-art and are widely used algorithms for face detection. Eigenfaces and Fisherfaces uses Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) respectively while LBPH uses histogram to recognize the face in the image. In this paper we have analyzed and compared the Eigenfaces, Local Binary pattern Histograms (LBPH) and Fisherfaces algorithms for different scenarios where there is high probability of getting errors. From the simulation results it has been observed that for these algorithms there is increases in the error rate whenever there is a change in the environment, lighting condition, hair and moustache change etc. in the face. Moreover, from the results it has been found that Eigenfaces and Fisherfaces are more prone to the errors than the LBPH.

关键词： Face recognition face detection principal component analysis PCA local binary pattern Eigenfaces Fisherfaces LBPH

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Business Models for Emerging Technologies: the Case of Affective computing 8

Business Models for Emerging Technologies: The Case of Affec...

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8th international conference on Affective computing and Intelligent Interaction (ACII)

作者： Ignatyeva, Olga Sokolov, Dmitry Lukashenko, Olga Shalakitskaia, Aleksandra Denef, Sebastian Samsonowa, Tatjana Int Inst Res Performance & Innovat Management eV IPERF Berlin Germany St Petersburg State Univ Grad Sch Management St Petersburg Russia Innopolis Univ Innopolis Russia OWN Space Berlin Germany

ISBN: (纸本)9781728138916

this paper explores the key features of disruptive business models in the affective computing industry, where particular business benefit and technological value are yet to be discovered. We designed the business model canvas for emotion recognition (ER) solutions based on analysis of 80 companies from secondary sources, as well as six case studies that we conducted ourselves. Based on these insights, our research highlights the elements in each block of the business model canvas that are typical for emerging technologies, namely not fully understood value proposition, B2B customer segment, free demos and trials in customer relationship, SaaS and technology licensing in revenue streams, investors and academia as key partners and R&D as key activity. We designed the canvas as a tool useful for anybody creating or analyzing ventures in emerging tech industries and, in particular, ER solutions. Our study contributes to the existing literature on disruptive business models for technological innovations by consolidating existing practices of ER sector and emphasizing on important patterns for emerging tech industries in general.

关键词： Innovation Emerging Technologies Disruptive Business Models Artificial Intelligence Affective computing

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Artificial Life Intelligence for Individual and Societal Accomplishment 18

Artificial Life Intelligence for Individual and Societal Acc...

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18th IEEE international conference on Cognitive Informatics and Cognitive computing (ICCI*CC)

作者： Ramanathan, Janani Mothers Serv Soc Pondicherry India

ISBN: (纸本)9781728114194

this paper explores the potential of the rapidly evolving fields of Natural Language Processing and Affective computing and proposes future applications that combine the power of both fields to assist individuals in their personal and collective accomplishment. It studies the latest developments in the field of Emotion Detection and recognition from facial expression, voice and text and discusses the shortcomings in current analysis systems. Human subjectivity is key to every choice, decision and act of individuals, and a comprehensive knowledge of human psychology is essential for effective analysis. As Emotional AI transcends the physical parameters and moves closer to understanding the emotional and mental human being in future, and Deep Learning enables greater comprehension of unstructured textual and audio-visual data, Cognitive computing can employ big data processing to assist humans in acquiring scholarship, anticipating social trends and even understanding life. the paper concludes with a proposal for a revolutionary field of Artificial Life Intelligence that can promote universal human welfare.

关键词： Affective computing Emotional AI Natural Language Processing Natural Language Understanding Big Data Processing pattern recognition Human Psychology Principles ofAccomplishment Social Evolution Character ofLife

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Local Binary patterning Approach for Movement Related Potentials based Brain Computer Interface 8

Local Binary Patterning Approach for Movement Related Potent...

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8th IEEE international Workshop on Advances in Sensors and Interfaces (IWASI)

作者： Mezzina, Giovanni De Venuto, Daniela Politecn Bari Dept Elect & Informat Engn Via E Orabona 4 I-70125 Bari Italy

ISBN: (纸本)9781728105567

this paper proposes the design and the implementation of an innovative algorithm for a 2-choices synchronous Brain-Computer Interface (BCI). the proposed BCI operates on signals from eight EEG channels evenly distributed along the sensorimotor area. the acquired EEGs are then analyzed by using a symbolization method. Typically, the symbolization includes data-analysis algorithms that translate physical processes from experimental measurements into a series of discrete symbols (e.g., bit strings). For the BCI application, the chosen symbolization algorithm is the Local Binary pattern (LBP). Since the selected LBP method uses binary operations for the whole processing chain (end-to-end), the complexity and the computing timing of the features extraction (FE) and real-time classification stages have been strongly reduced. Finally, a time-continuous Support Vector Machine (tcSVM) classifies the LBP-extracted features. the here proposed BCI algorithm has been validated on 3 subjects (aged 26 +/- 1), who underwent a stimulation protocol oriented to Movement-Related Potentials (MRPs) elicitation. the in-vivo validation showed how the system is able to reach an intention recognition accuracy of 85.61 +/- 1.19 %. In addition, starting from the complete data storage, the whole implemented computing chain asks, on average, for just similar to 3ms to provide the classification. As a proof of concept, the tcSVM outcomes have been used to drive, via Bluetooth, a 3D printed robotic hand.

关键词： Brain Computer Interface EEG Local Binary pattern Symbolization Robotic Hand

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Research on Security Protection Technology System of Power internet of things 8

Research on Security Protection Technology System of Power i...

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IEEE 8th Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Gao, Peng Yang, Ruxia Shi, Congcong Zhang, Xiaojian Global Energy Interconnect Res Inst State Grid Key Lab Informat & Network Secur Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538681787

With the rapid development of Internet of things applications, the power Internet of things technologies and applications covering the various production links of the power grid "transmission, transmission, transformation, distribution and use" are becoming more and more popular, and the terminal, network and application security risks brought by them are receiving more and more attention.. Combined with the architecture and risk of power Internet of things, this paper first proposes the overall security protection technology system and strategy for power Internet of things;then analyzes terminal identity authentication and authority control, edge area autonomy and data transmission protection, and application layer cloud fog security management. And the whole process real-time security monitoring;Finally, through the analysis of security risks and protection, the technical difficulties and directions for the security protection of the Internet of things are proposed.

关键词： Power Internet of things network security privacy protection edge computing fog calculation security monitoring

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