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 De-Shuang Huang
Kang-Hyun Jo
Ling Wang (Eds.)

Intelligent
LNAI 8589

Computing
Methodologies
10th International Conference, ICIC 2014
Taiyuan, China, August 3–6, 2014
Proceedings

123
Lecture Notes in Artificial Intelligence 8589

Subseries of Lecture Notes in Computer Science

LNAI Series Editors

Randy Goebel
University of Alberta, Edmonton, Canada
Yuzuru Tanaka
Hokkaido University, Sapporo, Japan
Wolfgang Wahlster
DFKI and Saarland University, Saarbrücken, Germany

LNAI Founding Series Editor

Joerg Siekmann
DFKI and Saarland University, Saarbrücken, Germany
De-Shuang Huang Kang-Hyun Jo
Ling Wang (Eds.)

Intelligent
Computing
Methodologies
10th International Conference, ICIC 2014
Taiyuan, China, August 3-6, 2014
Proceedings

13
Volume Editors
De-Shuang Huang
Tongji University
Machine Learning and Systems Biology Laboratory
School of Electronics and Information Engineering
4800 Caoan Road, Shanghai 201804, China
E-mail: dshuang@tongji.edu.cn
Kang-Hyun Jo
University of Ulsan
School of Electrical Engineering
680-749 No. 7-413, San 29, Muger Dong, Ulsan, South Korea
E-mail: jokanghyun@gmail.com
Ling Wang
Tsinghua University
Department of Automation
Bejing, China
E-mail: wangling@tsinghua.edu.cn

ISSN 0302-9743 e-ISSN 1611-3349

ISBN 978-3-319-09338-3 e-ISBN 978-3-319-09339-0
DOI 10.1007/978-3-319-09339-0
Springer Cham Heidelberg New York Dordrecht London

Library of Congress Control Number: 2014943591

LNCS Sublibrary: SL 7 – Artificial Intelligence

© Springer International Publishing Switzerland 2014
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 Preface

The International Conference on Intelligent Computing (ICIC) was started to

provide an annual forum dedicated to the emerging and challenging topics in
artificial intelligence, machine learning, pattern recognition, bioinformatics, and
computational biology. It aims to bring together researchers and practitioners
from both academia and industry to share ideas, problems, and solutions related
to the multifaceted aspects of intelligent computing.
ICIC 2014, held in Taiyuan, China, during August 3–6, 2014, constituted
the 10th International Conference on Intelligent Computing. It built upon the
success of ICIC 2013, ICIC 2012, ICIC 2011, ICIC 2010, ICIC 2009, ICIC 2008,
ICIC 2007, ICIC 2006, and ICIC 2005 that were held in Nanning, Huangshan,
Zhengzhou, Changsha, China, Ulsan, Korea, Shanghai, Qingdao, Kunming, and
Hefei, China, respectively.
This year, the conference concentrated mainly on the theories and method-
ologies as well as the emerging applications of intelligent computing. Its aim was
to unify the picture of contemporary intelligent computing techniques as an in-
tegral concept that highlights the trends in advanced computational intelligence
and bridges theoretical research with applications. Therefore, the theme for this
conference was “Advanced Intelligent Computing Technology and Ap-
plications”. Papers focused on this theme were solicited, addressing theories,
methodologies, and applications in science and technology.
ICIC 2014 received 667 submissions from 21 countries and regions. All pa-
pers went through a rigorous peer-review procedure and each paper received at
least three review reports. Based on the review reports, the Program Committee
finally selected 235 high-quality papers for presentation at ICIC 2013, included
in three volumes of proceedings published by Springer: one volume of Lecture
Notes in Computer Science (LNCS), one volume of Lecture Notes in Artificial
Intelligence (LNAI), and one volume of Lecture Notes in Bioinformatics (LNBI).
This volume of Lecture Notes in Artificial Intelligence (LNAI) includes 85
papers.
The organizers of ICIC 2014, including Tongji University and North Univer-
sity of China, Taiyuan Normal University, Taiyuan University of Science and
Technology, made an enormous effort to ensure the success of the conference.
We hereby would like to thank the members of the Program Committee and
the referees for their collective effort in reviewing and soliciting the papers. We
would like to thank Alfred Hofmann, executive editor from Springer, for his frank
and helpful advice and guidance throughout and for his continuous support in
publishing the proceedings. In particular, we would like to thank all the authors
for contributing their papers. Without the high-quality submissions from the
VI Preface

authors, the success of the conference would not have been possible. Finally,
we are especially grateful to the IEEE Computational Intelligence Society, the
International Neural Network Society, and the National Science Foundation of
China for their sponsorship.

May 2014 De-Shuang Huang

Kang-Hyun Jo
Ling Wang
 ICIC 2014 Organization

General Co-chairs

De-Shuang Huang, China Jiye Liang, China

Vincenzo Piuri, Italy Jianchao Zeng, China
Yan Han, China

Program Committee Co-chairs

Kang Li, UK
Juan Carlos Figueroa, Colombia

Organizing Committee Co-chairs

Kang-Hyun Jo, Korea Bing Wang, China
Valeriya Gribova, Russia Xing-Ming Zhao, China

Award Committee Chair

Vitoantonio Bevilacqua, Italy

Publication Chair
Phalguni Gupta, India

Workshop/Special Session Co-chairs

Jiang Qian, USA

Zhongming Zhao, USA

Special Issue Chair

M. Michael Gromiha, India
VIII ICIC 2014 Organization

Tutorial Chair
Laurent Heutte, France

International Liaison
Prashan Premaratne, Australia

Publicity Co-chairs

Kyungsook Han, Korea Abir Hussain, UK

Ling Wang, China Zhi-Gang Zeng, China

Exhibition Chair
Chun-Hou Zheng, China

Program Committee Members

Khalid Aamir, Pakistan Minrui Fei, China

Andrea F. Abate, USA Juan Carlos Figueroa-Garcı́a,
Sabri Arik, Korea Colombia
Vasily Aristarkhov, Australia shan Gao, China
Costin Badica, Japan Liang Gao, China
Waqas Bangyal, Pakistan Dun-wei Gong, India
Vitoantonio Bevilacqua, Italy Valeriya Gribova, China
Shuhui Bi, China Michael Gromiha, China
Jair Cervantes, Mexico Xingsheng Gu, China
Yuehui Chen, China Kayhan Gulez, USA
Qingfeng Chen, China Ping Guo, China
Wen-Sheng Chen, China Phalguni Gupta, India
Xiyuan Chen, China Kyungsook Han, Korea
Guanling Chen, USA Fei Han, China
Yoonsuck Choe, USA Laurent Heutte, France
Ho-Jin Choi, Korea, Republic of Wei-Chiang Hong, Taiwan
Michal Choras, Colombia Yuexian Hou, China
Angelo Ciaramella, China Jinglu Hu, China
Youping Deng, Japan Tingwen Huang, Qatar
Primiano Di Nauta, Italy Peter Hung, Taiwan
Salvatore Distefano, USA Abir Hussain, UK
Ji-Xiang Du, China Saiful Islam, India
Jianbo Fan, China Li Jia, China
 ICIC 2014 Organization IX

Zhenran Jiang, China Dinggang Shen, USA

Kang-Hyun Jo, Korea Fanhuai Shi, China
Dah-Jing Jwo, Korea Shitong Wang, China
Seeja K.R, India Wilbert Sibanda, USA
Vandana Dixit Kaushik, India Jiatao Song, China
Gul Muhammad Khan, Pakistan Stefano Squartini, Italy
Sungshin Kim, Korea Badrinath Srinivas, USA
Donald Kraft, USA Zhan-Li Sun, China
Yoshinori Kuno, Japan Evi Syukur, USA
Takashi Kuremoto, Japan Joaquı́n Torres-Sospedra, Spain
Jaerock Kwon, USA Rua-Huan Tsaih, USA
Vincent Lee, Australia Antonio Uva, USA
Shihua Zhang, China Jun Wan, USA
Guo-Zheng Li, China Yong Wang, China
Xiaodi Li, China Ling Wang, China
Bo Li, China Jim Jing-Yan Wang, USA
Kang Li, UK Xuesong Wang, China
Peihua Li, China Bing Wang, China
Jingjing Li, USA Ze Wang, USA
Yuhua Li, UK Junwen Wang, HK
Honghuang Lin, USA Hong Wei, UK
Meiqin Liu, USA Wei Wei, Norway
Ju Liu, China Yan Wu, China
Xiwei Liu, China QingXiang Wu, China
Shuo Liu, China Junfeng Xia, China
Yunxia Liu, China Shunren Xia, China
Chu Kiong Loo, Mexico Bingji Xu, China
Zhao Lu, USA Gongsheng xu, China
Ke Lu, China Yu Xue, China
Yingqin Luo, USA Xin Yin, USA
Jinwen Ma, USA Xiao-Hua Yu, USA
Xiandong Meng, China Zhigang Zeng, China
Filippo Menolascina, Italy Shihua Zhang, China
Ivan Vladimir Meza-Ruiz, Australia Jun Zhang, China
Tarik Veli Mumcu Mumcu, Turkey Xing-Ming Zhao, China
Roman Neruda, Turkey Hongyong Zhao, China
Ben Niu, China Xiaoguang Zhao, China
Seiichi Ozawa, Korea Zhongming Zhao, USA
Paul Pang, China Bojin Zheng, China
Francesco Pappalardo, USA Chunhou Zheng, China
Surya Prakash, India Fengfeng Zhou, China
Prashan Premaratne, Australia Yongquan Zhou, China
Daowen Qiu, China Hanning Zhou, China
Angel Sappa, USA Li Zhuo, China
Li Shang, China Xiufen Zou, China
X ICIC 2014 Organization

Reviewers

Jakub Šmı́d Giuseppe Carbone

Pankaj Acharya Raffaele Carli
Erum Afzal Jair Cervantes
Parul Agarwal Aravindan Chandrabose
Tanvir Ahmad Yuchou Chang
Musheer Ahmad Deisy Chelliah
Syed Ahmed Gang Chen
Sabooh Ajaz Songcan Chen
Haya Alaskar Jianhung Chen
Felix Albu David Chen
Dhiya Al-Jumeily Hongkai Chen
Israel Alvarez Villalobos Xin Chen
Muhammad Amjad Fanshu Chen
Ning An Fuqiang Chen
Mary Thangakani Anthony Bo Chen
Masood Ahmad Arbab Xin Chen
Soniya be Liang Chen
Sunghan Bae Wei Chen
Lukas Bajer Jinan Chen
Waqas Bangyal Yu Chen
Gang Bao Junxia Cheng
Donato Barone Zhang Cheng
Silvio Barra Feixiong Cheng
Alex Becheru Cong Cheng
Ye Bei Han Cheng
Mauri Benedito Bordonau Chi-Tai Cheng
Simon Bernard Chengwang Xie
Vitoantonio Bevilacqua Seongpyo Cheon
Ying Bi Ferdinando Chiacchio
Ayse Humeyra Bilge Cheng-Hsiung Chiang
Honghua Bin Wei Hong Chin
Jun Bo Simran Choudhary
Nora Boumella Angelo Ciaramella
Fabio Bruno Azis Ciayadi
Antonio Bucchiarone Rudy Ciayadi
Danilo Caceres Danilo Comminiello
Yiqiao Cai Carlos Cubaque
Qiao Cai Yan Cui
Guorong Cai Bob Cui
Francesco Camastra Cuco Curistiana
Mario Cannataro Yakang Dai
Kecai Cao Dario d’Ambruoso
Yi Cao Yang Dan
 ICIC 2014 Organization XI

Farhan Dawood Francesco Ferrise

Francesca De Crescenzio Juan Carlos Figueroa
Kaushik Deb Michele Fiorentino
Saverio Debernardis Carlos Franco
Dario Jose Delgado-Quintero Gibran Fuentes Pineda
Sara Dellantonio Hironobu Fujiyoshi
Jing Deng Kazuhiro Fukui
Weilin Deng Wai-Keung Fung
M.C. Deng Chun Che Fung
Suping Deng Chiara Galdi
Zhaohong Deng Jian Gao
Somnath Dey Yushu Gao
Yunqiang Di Liang Gao
Hector Diez Rodriguez Yang Gao
Rong Ding Garcia-Lamont Farid
Liya Ding Garcia-Marti Irene
Sheng Ding Michele Gattullo
Sheng Ding Jing Ge
Shihong Ding Na Geng
Dayong Ding Shaho Ghanei
Xiang Ding Rozaida Ghazali
Salvatore Distefano Rosalba Giugno
Chelsea Dobbins Fengshou Gu
Xueshi Dong Tower Gu
Vladislavs Dovgalecs Jing Gu
Vlad Dovgalecs Smile Gu
Gaixin Du Guangyue Du
Dajun Du Weili Guo
Kaifang Du Yumeng Guo
Haibin Duan Fei Guo
Durak-Ata Lutfiye Tiantai Guo
Malay Dutta Yinan Guo
Tolga Ensari Yanhui Guo
Nicola Epicoco Chenglin Guo
Marco Falagario Lilin Guo
Shaojing Fan Sandesh Gupta
Ming Fan Puneet Gupta
Fenghua Fan Puneet Gupta
Shaojing Fan Shi-Yuan Han
Yaping Fang Fei Han
Chen Fei Meng Han
Liangbing Feng Yu-Yan Han
Shiguang Feng Zhimin Han
Guojin Feng Xin Hao
Alessio Ferone Manabu Hashimoto
XII ICIC 2014 Organization

Tao He Xu Jie
Selena He Jiening Xia
Xing He Taeseok Jin
Feng He Jingsong Shi
Van-Dung Hoang Mingyuan Jiu
Tian Hongjun Kanghyun Jo
Lei Hou Jayasudha John Suseela
Jingyu Hou Ren Jun
Ke Hu Fang Jun
Changjun Hu Li Jun
Zhaoyang Hu Zhang Junming
Jin Huang Yugandhar K.
Qiang Huang Tomáš Křen
Lei Huang Yang Kai
Shin-Ying Huang Hee-Jun Kang
Ke Huang Qi Kang
Huali Huang Dong-Joong Kang
Jida Huang Shugang Kang
Xixia Huang Bilal Karaaslan
Fuxin Huang Rohit Katiyar
Darma Putra i Ketut Gede Ondrej Kazik
Haci Ilhan Mohd Ayyub Khan
Sorin Ilie Muhammed Khan
Saiful Islam Sang-Wook Kim
Saeed Jafarzadeh Hong-Hyun Kim
Alex James One-Cue Kim
Chuleerat Jaruskulchai Duangmalai Klongdee
James Jayaputera Kunikazu Kobayashi
Umarani Jayaraman Yoshinori Kobayashi
Mun-Ho Jeong Takashi Komuro
Zhiwei Ji Toshiaki Kondo
Shouling Ji Deguang Kong
Yafei Jia Kitti Koonsanit
Hongjun Jia Rafal Kozik
Xiao Jian Kuang Li
Min Jiang Junbiao Kuang
Changan Jiang Baeguen Kwon
Tongyang Jiang Hebert Lacey
Yizhang Jiang Chunlu Lai
He Jiang Chien-Yuan Lai
Yunsheng Jiang David Lamb
Shujuan Jiang Wei Lan
Ying Jiang Chaowang Lan
Yizhang Jiang Qixun Lan
Changan Jiang Yee Wei Law
 ICIC 2014 Organization XIII

Tien Dung Le Rong Liu

My-Ha Le Liang Liu
Yongduck Lee Yufeng Liu
Jooyoung Lee Qing Liu
Seokju Lee Zhe Liu
Shao-Lun Lee Zexian Liu
Xinyu Lei Li Liu
Gang Li Shiyong Liu
Yan Li Sen Liu
Liangliang Li Qi Liu
Xiaoguang Li Jin-Xing Liu
Zheng Li Xiaoming Liu
Huan Li Ying Liu
Deng Li Xiaoming Liu
Ping Li Bo Liu
Qingfeng Li Yunxia Liu
Fuhai Li Alfredo Liverani
Hui Li Anthony Lo
Kai Li Lopez-Chau Asdrúbal
Longzhen Li Siow Yong Low
Xingfeng Li Zhen Lu
Jingfei Li Xingjia Lu
Jianxing Li Junfeng Luo
Keling Li Juan Luo
Juan Li Ricai Luo
Jianqing Li Youxi Luo
Yunqi Li Yanqing Ma
Bing Nan Li Wencai Ma
Lvzhou Li Lan Ma
Qin Li Chuang Ma
Xiaoguang Li Xiaoxiao Ma
Xinwu Liang Sakashi Maeda
Jing Liang Guoqin Mai
Li-Hua Zhang Mario Manzo
Jongil Lim Antonio Maratea
Changlong Lin Erik Marchi
Yong Lin Carlos Román Mariaca Gaspar
Jian Lin Naoki Masuyama
Genie Lin Gu Meilin
Ying Liu Geethan Mendiz
Chenbin Liu Qingfang Meng
James Liu Filippo Menolascina
Liangxu Liu Muharrem Mercimek
Yuhang Liu Giovanni Merlino
Liang Liu Hyeon-Gyu Min
XIV ICIC 2014 Organization

Martin Renqiang Min Ali Qamar

Minglei Tong Xiangbo Qi
Saleh Mirheidari Shijun Qian
Akio Miyazaki Pengjiang Qian
Yuanbin Mo Bin Qian
Quanyi Mo Ying Qiu
Andrei Mocanu Jian-Ding Qiu
Raffaele Montella Junfeng Qu
Montoliu Raul Junjun Qu
Tsuyoshi Morimoto Muhammad Rahman
Mohamed Mousa Alzawi Sakthivel Ramasamy
Lijun Mu Tao Ran
Inamullah Muhammad Martin Randles
Izharuddin Muhammed Caleb Rascon
Tarik Veli Mumcu Muhammad Rashid
Francesca Nardone Haider Raza
Fabio Narducci David Reid
Rodrigo Nava Fengli Ren
Patricio Nebot Stefano Ricciardi
Ken Nguyen Angelo Riccio
Changhai Nie Alejo Roberto
Li Nie Abdus Samad
Aditya Nigam Ruya Samli
Evgeni Nurminski Hongyan Sang
Kok-Leong Ong Michele Scarpiniti
Kazunori Onoguchi Dongwook Seo
Zeynep Orman Shi Sha
Selin Ozcira Elena Shalfeeva
Cuiping Pan Li Shang
Binbin Pan Linlin Shen
Quan-Ke Pan Yehu Shen
Dazhao Pan Haojie Shen
Francesco Pappalardo Jin Biao Shen
Jekang Park Ajitha Shenoy
Anoosha Paruchuri Jiuh-Biing Sheu
Vibha Patel Xiutao Shi
Samir Patel Jibin Shi
Lizhi Peng Fanhuai Shi
Yiming Peng Yonghong Shi
Jialin Peng Yinghuan Shi
Klara Peskova Atsushi Shimada
Caroline Petitjean Nobutaka Shimada
Martin Pilat Ji Sun Shin
Surya Prakash Ye Shuang
Philip Pretorius Raghuraj Singh
 ICIC 2014 Organization XV

Dushyant Kumar Singh Andrysiak Tomasz

Haozhen Situ Torres-Sospedra Joaquı́n
Martin Slapak Sergi Trilles
Sergey Smagin Yao-Hong Tsai
Yongli Song Naoyuki Tsuruta
Yinglei Song Fahad Ullah
Meiyue Song Pier Paolo Valentini
Bin Song Andrey Vavilin
Rui Song Giuseppe Vettigli
Guanghua Song Petra Vidnerová
Gang Song Villatoro-Tello Esaú
Sotanto Sotanto Ji Wan
Sreenivas Sremath Tirumala Li Wan
Antonino Staiano Lin Wan
Jinya Su Quan Wang
Hung-Chi Su Zixiang Wang
Marco Suma Yichen Wang
Xiaoyan Sun Xiangjun Wang
Jiankun Sun Yunji Wang
Sheng Sun Hong Wang
Yu Sun Jinhe Wang
Celi Sun Xuan Wang
Yonghui Sun Xiaojuan Wang
Zengguo Sun Suyu Wang
Jie Sun Zhiyong Wang
Aboozar Taherkhani Xiangyu Wang
Shinya Takahashi Mingyi Wang
Jinying Tan Yan Wang
Shijun Tang Zongyue Wang
Xiwei Tang Huisen Wang
Buzhou Tang Yongcui Wang
Ming Tang Xiaoming Wang
Jianliang Tang Zi Wang
Hissam Tawfik Jun Wang
Zhu Teng Aihui Wang
Sin Teo Yi Wang
Girma Tewolde Ling Wang
Xiange Tian Zhaoxi Wang
Yun Tian Shulin Wang
Tian Tian Yunfei Wang
Hao Tian Yongbo Wang
Gao Tianshun Zhengxiang Wang
Kamlesh Tiwari Sheng-Yao Wang
Amod Tiwari Jingchuan Wang
Kamlesh Tiwari Qixin Wang
XVI ICIC 2014 Organization

Yong Wang Jin Xu

Fang-Fang Wang Xin Xu
Tian Wang Meng Xu
Zhenzhong Wang Li Xu
Panwen Wang Feng Xu
Lei Wang Zhenyu Xuan
Qilong Wang Hari Yalamanchili
Dong Wang Atsushi Yamashita
Ping Wang Mingyuan Yan
Huiwei Wang Yan Yan
Yiqi Wang Zhigang Yan
Zhixuan Wei Bin Yan
Zhihua Wei Zhile Yang
Li Wei Dan Yang
Shengjun Wen Yang Yang
Shiping Wen Wankou Yang
Di Wu Wenqiang Yang
Yonghui Wu Yuting Yang
Chao Wu Chia-Luen Yang
Xiaomei Wu Chyuan-Huei Yang
Weili Wu Deng Yanni
Hongrun Wu Jin Yao
Weimin Wu Xiangjuan Yao
Guolong Wu Tao Ye
Siyu Xia Xu Ye
Qing Xia Fengqi Yi
Sen Xia Wenchao Yi
Jin Xiao Kai Yin
Min Xiao James j.q. Yu
Qin Xiao Helen Yu
Yongfei Xiao Jun Yu
Zhao Xiaoguang Fang Yu
Zhuge Xiaozhong Xu Yuan
Minzhu Xie Lin Yuan
Zhenping Xie Jinghua Yuan
Jian Xie Lin Yuling
Ting Xie Faheem Zafari
Chao Xing Xue-Qiang Zeng
Wei Xiong Haimao Zhan
Hao Xiong Yong-Wei Zhang
Yi Xiong Jing Zhang
Xiaoyin Xu Shuyi Zhang
Dawen Xu Kevin Zhang
Jing Xu Ming Zhang
Yuan Xu Zhenmin Zhang
 ICIC 2014 Organization XVII

Xuebing Zhang Yunlong Zhao

Minlu Zhang Miaomiao Zhao
Jianping Zhang Xinhua Zhao
Xiaoping Zhang Xu Zhao
Yong Zhang Guodong Zhao
Qiang Zhang Liang Zhao
Guohui Zhang Feng Zhao
Chunhui Zhang Juan Zhao
Yifeng Zhang Junfei Zhao
Wenxi Zhang Changbo Zhao
Xiujun Zhang Yue Zhao
Long Zhang Min Zheg
Jian Zhang Dong Zhen
Boyu Zhang Guang Zheng
Hailei Zhang Xiaolong Zheng
Hongyun Zhang Huanyu Zheng
Jianhua Zhang Shenggen Zheng
Chunjiang Zhang Shan Zhong
Peng Zhang Qi Zhou
Jianhai Zhang Mian Zhou
Hongbo Zhang Yinzhi Zhou
Lin Zhang Jiayin Zhou
Xiaoqiang Zhang Songsheng Zhou
Haiying Zhang Bo Zhou
Jing Zhang Qiang Zhou
Wei Zhang Lei Zhu
Qian Zhang Lin Zhu
Hongli Zhang Yongxu Zhu
Guohui Zhang Nanli Zhu
Liping Zhang Xiaolei Zhu
Hongbo Zhang Majid Ziaratban
Sen Zhao Xiangfu Zou
Yaou Zhao Brock Zou
Jane Zhao Tanish
Liang Zhao Qiqi Duan
 Table of Contents

Soft Computing
Affective Tutoring System for Android Mobiles . . . . . . . . . . . . . . . . . . . . . . 1
Ramón Zatarain-Cabada, M.L. Barrón-Estrada,
José Luis Olivares Camacho, and Carlos A. Reyes-Garcı́a

Solving Three-Objective Flow Shop Problem with Fast Hypervolume-

Based Local Search Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Rong-Qiang Zeng and Ming-Sheng Shang

Artificial Bee Colony Algorithms

A Learning Automata-Based Singular Value Decomposition and Its
Application in Recommendation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Yuchun Jing, Wen Jiang, Guiyang Su, Zhisheng Zhou, and
Yifan Wang

A Novel 2-Stage Combining Classifier Model with Stacking and Genetic

Algorithm Based Feature Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Tien Thanh Nguyen, Alan Wee-Chung Liew,
Xuan Cuong Pham, and Mai Phuong Nguyen

Improved Bayesian Network Structure Learning with Node Ordering

via K2 Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Zhongqiang Wei, Hongzhe Xu, Wen Li, Xiaolin Gui, and
Xiaozhou Wu

Combining Multi Classifiers Based on a Genetic Algorithm –

A Gaussian Mixture Model Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Tien Thanh Nguyen, Alan Wee-Chung Liew, Minh Toan Tran, and
Mai Phuong Nguyen

Unsupervised Learning
A Precise Hard-Cut EM Algorithm for Mixtures of Gaussian
Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Ziyi Chen, Jinwen Ma, and Yatong Zhou

Comparison of EM-Based Algorithms and Image Segmentation

Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
Mei Niu, Qinpei Zhao, and Hongyu Li
XX Table of Contents

Artificial Curiosity Driven Robots with Spatiotemporal Regularity

Discovery Ability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Davood Kalhor and Chu Kiong Loo

Kernel Methods and Supporting Vector Machines

The Equivalence Relationship between Kernel Functions Based on
SVM and Four-Layer Functional Networks . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Yongquan Zhou, Qifang Luo, Mingzhi Ma, and Liangliang Li
Multiple Kernel Learning Based on Cooperative Clustering . . . . . . . . . . . . 107
Haiyang Du, Chuanhuan Yin, and Shaomin Mu

Machine Learning
Automatic Non-negative Matrix Factorization Clustering with
Competitive Sparseness Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Chenglin Liu and Jinwen Ma
Fusing Decision Trees Based on Genetic Programming for Classification
of Microarray Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
KunHong Liu, MuChenxuan Tong, ShuTong Xie, and ZhiHao Zeng
A Study of Data Classification and Selection Techniques for Medical
Decision Support Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Ahmed J. Aljaaf, Dhiya Al-Jumeily, Abir J. Hussain, David Lamb,
Mohammed Al-Jumaily, and Khaled Abdel-Aziz
A Reduction SVM Classification Algorithm Based on Adaptive AP
Clustering Granulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Xiuxi Wei
Learning Automata Based Cooperative Student-Team in Tutorial-Like
System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
Yifan Wang, Wen Jiang, Yinghua Ma, Hao Ge, and Yuchun Jing
Clustering-Based Latent Variable Models for Monocular Non-rigid 3D
Shape Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Quan Wang, Fei Wang, Daming Li, and Xuan Wang
Comments-Attached Chinese Microblog Sentiment Classification Based
on Machine Learning Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Bo Yan, Bin Zhang, Hongyi Su, and Hong Zheng
Evaluation of Resonance in Staff Selection through Multimedia
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Vitoantonio Bevilacqua, Angelo Antonio Salatino, Carlo Di Leo,
Dario D’Ambruoso, Marco Suma, Donato Barone, Giacomo Tattoli,
Domenico Campagna, Fabio Stroppa, and Michele Pantaleo
 Table of Contents XXI

Using Rough Set Theory and Decision Trees to Diagnose Enterprise

Distress – Consideration of Corporate Governance Variables . . . . . . . . . . . 199
Fu Hsiang Chen, Der-Jang Chi, and Chun-Yi Kuo

Fuzzy Theory and Algorithms

Fuzzy Propositional Logic System and Its λ-Resolution . . . . . . . . . . . . . . . 212
Jiexin Zhao and Zhenghua Pan

Multi-level Linguistic Fuzzy Decision Network Hierarchical Structure

Model for MCDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
Basem Mohamed Elomda, Hesham Ahmed Hefny,
Maryam Hazman, and Hesham Ahmed Hassan

An Edge Sensing Fuzzy Local Information C-Means Clustering

Algorithm for Image Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
Xinning Wang, Xiangbo Lin, and Zhen Yuan

Application of Genetic Algorithm and Fuzzy Gantt Chart to Project

Scheduling with Resource Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
Yu-Chuan Liu, Hong-Mei Gao, Shih-Ming Yang, and
Chun-Yung Chuang

Dynamic Output Feedback Guaranteed Cost Control for T-S Fuzzy

Systems with Uncertainties and Time Delays . . . . . . . . . . . . . . . . . . . . . . . . 253
Guangfu Ma, Yanchao Sun, Jingjing Ma, Chuanjiang Li, and
Shuo Sun

Image Processing
Shape and Color Based Segmentation Using Level Set Framework . . . . . . 265
Xiang Gao, Ji-Xiang Du, Jing Wang, and Chuan-Min Zhai

An Integrated NRSFM Approach for Image Sequences with Small

Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
Ya-Ping Wang, Zhan-Li Sun, and Li Shang

Image Super-Resolution Reconstruction Based on Two-Stage Dictionary

Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
Li Shang and Zhan-li Sun

Intelligent Computing in Computer Vision

Position Accuracy Improvement of Robots having Closed-Chain
Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285
Hoai-Nhan Nguyen, Jian Zhou, Hee-Jun Kang, and Tien-Dung Le
XXII Table of Contents

GPU-Based Real-Time Range Image Segmentation . . . . . . . . . . . . . . . . . . . 293

Xinhua Jin, Dong Joong Kang, and Mun-Ho Jeong

Recognition of Human Action and Identification Based on SIFT and

Watermark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298
Khawlah Hussein Ali and Tianjiang Wang

Augmented Reality Surveillance System for Road Traffic Monitoring . . . . 310

Alexander Filonenko, Andrey Vavilin, Taeho Kim, and
Kang-Hyun Jo

Effective Palm Tracking with Integrated Tracker and Offline Detector . . . 318
Zhibo Yang, Yanmin Zhu, and Bo Yuan

Monocular 3D Shape Recovery of Inextensibility Deformable Surface

by Using DE-Based Niching Algorithm with Partial Reinitialization . . . . 328
Xuan Wang, Fei Wang, and Lei Chen

Computer Vision Based Traffic Monitoring System for Multi-track

Freeways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339
Zubair Iftikhar, Prashan Dissanayake, and Peter Vial

Robust Pose Estimation Algorithm for Approximate Coplanar

Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350
Haiwei Yang, Fei Wang, Lei Chen, Yicong He, and Yongjian He

A BP Neural Network Predictor Model for Stock Price . . . . . . . . . . . . . . . 362

Li Huo, Bo Jiang, Tao Ning, and Bo Yin

Intelligent Computing in Communication Networks

Plant Leaf Recognition Using Histograms of Oriented Gradients . . . . . . . 369
Qing Xia, Hao-Dong Zhu, Yong Gan, and Li Shang

An Implementation of an Intelligent PCE-Agent-Based Multi-domain

Optical Network Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
Ying Xu, Tiantian Zhang, and Renfa Li

A Heuristic Virtual Network Mapping Algorithm . . . . . . . . . . . . . . . . . . . . . 385

Xiao-guang Wang, Xiang-wei Zheng, and Dian-jie Lu

Fault-Tolerant Control, Fault Diagnosis and Recovery in Runtime

of Business Docking Service Composition Flow in the Cloud
Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396
Jianhua Han, Silu He, Hengxin Li, and Jianping Huang
 Table of Contents XXIII

Intelligent Image/Document Retrievals

Ambiguous Proximity Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
Quanquan Wang and Yongping Li
Indexing SURF Features by SVD Based Basis on GPU with
Multi-Query Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 422
Vibha Patel and Bhavin Patel

Intelligent Data Analysis and Prediction

Dynamically Changing Service Level Agreements (SLAs) Management
in Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 434
Waleed Halboob, Haider Abbas, Kamel Haouam, and Asif Yaseen
Foundry Material Design with Artificial Intelligence . . . . . . . . . . . . . . . . . . 444
Jingjing Zhao, Xingtong Liu, Afeng Yang, and Chun Du

Intelligent Agent and Web Applications

An Intelligent Agent Simulation Model to Evaluate Herd Behavior and
Sales Effort in a Duopoly Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456
Feng Li and Ying Wei
A “Content-Behavior” Learner Model for Adaptive Learning System . . . . 466
Qingchun Hu, Yong Huang, and Yi Li
Aggregate MAC Based Authentication for Secure Data Aggregation in
Wireless Sensor Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
Keyur Parmar and Devesh C. Jinwala

Intelligent Fault Diagnosis

Active Learning Methods for Classification of Hyperspectral Remote
Sensing Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484
Sheng Ding, Bo Li, and Xiaowei Fu
Time to Fault Minimization for Induction Motors Using Wavelet
Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492
Amirhossein Ghods and Hong-Hee Lee

Knowledge Representation/Reasoning
Legal Reasoning Engine for Civil Court Procedure . . . . . . . . . . . . . . . . . . . 500
Tanapon Tantisripreecha, Ken Satoh, and Nuanwan Soonthornphisaj
A Multimodal Fingers Classification for General Interactive Surfaces . . . 513
Vitoantonio Bevilacqua, Donato Barone, and Marco Suma
XXIV Table of Contents

A Signal Modulation Type Recognition Method Based on Kernel PCA

and Random Forest in Cognitive Network . . . . . . . . . . . . . . . . . . . . . . . . . . . 522
Xin Wang, Zhijun Gao, Yanhui Fang, Shuai Yuan, Haoxuan Zhao,
Wei Gong, Minghao Qiu, and Qiang Liu

Knowledge Discovery and Data Mining

Privacy-Preserving Data Mining Algorithm Based on Modified Particle
Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529
Lei Yang, Jue Wu, Lingxi Peng, and Feng Liu
Topic Extraction Based on Knowledge Cluster in the Field
of Micro-blog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542
Ming Li, Chunhong Zhang, Li Sun, and Xianlei Shao
Multi-strategy Based Sina Microblog Data Acquisition for Opinion
Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551
Xiao Sun, Jia-qi Ye, and Fu-ji Ren
Mining Longest Frequent Patterns with Low-Support Items . . . . . . . . . . . 561
Qinhua Huang and Weimin Ouyang
Integrating Time Stamps into Discovering the Places of Interest . . . . . . . . 571
Jun Zhou, Qinpei Zhao, and Hongyu Li
A Hybrid Solution of Mining Frequent Itemsets from Uncertain
Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581
Xiaomei Yu, Hong Wang, and Xiangwei Zheng
DVT-PKM: An Improved GPU Based Parallel K-Means Algorithm . . . . . 591
Bo Yan, Ye Zhang, Zijiang Yang, Hongyi Su, and Hong Zheng
A Multi-Intelligent Agent for Knowledge Discovery in Database
(MIAKDD): Cooperative Approach with Domain Expert for Rules
Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602
Mohammed Abbas Kadhim, M. Afshar Alam, and Harleen Kaur

Natural Language Processing and Computational

Linguistics
The Role of Pre-processing in Twitter Sentiment Analysis . . . . . . . . . . . . . 615
Yanwei Bao, Changqin Quan, Lijuan Wang, and Fuji Ren
Construction of a Chinese Emotion Lexicon from Ren-CECps . . . . . . . . . . 625
Lijuan Wang, Changqin Quan, Yanwei Bao, and Fuji Ren
Word Frequency Statistics Model for Chinese Base Noun Phrase
Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 635
Lu Kong, Fuji Ren, Xiao Sun, and Changqin Quan
 Table of Contents XXV

Structure Constrained Discriminative Non-negative Matrix

Factorization for Feature Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 645
Yan Jin, Lisi Wei, Yugen Yi, and Jianzhong Wang

Next-Gen Sequencing and Metagenomics

Simulated Annealing Based Algorithm for Mutated Driver Pathways
Detecting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 658
Chao Yan, Hai-Tao Li, Ai-Xin Guo, Wen Sha, and Chun-Hou Zheng

Special Session on Intelligent Computing in

Scheduling and Engineering Optimization
A Grouped Fruit-Fly Optimization Algorithm for the No-Wait Lot
Streaming Flow Shop Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664
Peng Zhang and Ling Wang
An Enhanced Estimation of Distribution Algorithm for No-Wait Job
Shop Scheduling Problem with Makespan Criterion . . . . . . . . . . . . . . . . . . . 675
Shao-Feng Chen, Bin Qian, Rong Hu, and Zuo-Cheng Li
A Bayesian Statistical Inference-Based Estimation of Distribution
Algorithm for the Re-entrant Job-Shop Scheduling Problem with
Sequence-Dependent Setup Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686
Shao-Feng Chen, Bin Qian, Bo Liu, Rong Hu, and
Chang-Sheng Zhang
An Effective Estimation of Distribution Algorithm for Multi-track
Train Scheduling Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697
Shengyao Wang and Ling Wang

Special Session on Advanced Modeling, Control and

Optimization Techniques for Complex Engineering
Systems
Construction of Basic Education Cloud Computing Platform Based on
Virtualization Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 709
Minghui Zhang and Jinchen Zhou
A New Compact Teaching-Learning-Based Optimization Method . . . . . . . 717
Zhile Yang, Kang Li, and Yuanjun Guo
ANFIS Modeling of PMV Based on Hierarchical Fuzzy System . . . . . . . . . 727
Yifan Luo, Ning Li, and Shaoyuan Li
Static Security Risk Assessment with Branch Outage Considering the
Dependencies among Input Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739
Xue Li, Xiong Zhang, and Dajun Du
XXVI Table of Contents

On Spacecraft Relative Orbital Motion Based on Main-Flying Direction

Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 751
Yanchao Sun, Huixiang Ling, Chuanjiang Li, Guangfu Ma, and
Wenrui Zhao

Special Session on Complex Networks and Their

Applications

Community Detection Method of Complex Network Based on ACO

Pheromone of TSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 763
Si Liu, Cong Feng, Ming-Sheng Hu, and Zhi-Juan Jia

Complex Network Construction Method of Disaster Regional

Association Based on Optimized Compressive Sensing . . . . . . . . . . . . . . . . 771
Si Liu, Cong Feng, Zhi-Juan Jia, and Ming-Sheng Hu

Cascading Failures in Power Grid under Three Node Attack

Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 779
Sui-Min Jia, Yun-Ye Wang, Cong Feng, Zhi-Juan Jia, and
Ming-Sheng Hu

Dynamical Distribution of Capacities Strategy for Suppressing

Cascading Failure in Power Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 787
Zhi-Juan Jia, Yu Zhang, Cong Feng, and Ming-Sheng Hu

Pinning Control of Asymmetrically Coupled Complex Dynamical

Network with Heterogeneous Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 795
Fengli Ren and Hongyong Zhao

Particle Swarm Optimizations for Multi-type Vehicle Routing Problem

with Time Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 808
Xiaobin Gan, Junbiao Kuang, and Ben Niu

Special Session on Time Series Forecasting and

Analysis Using Artificial Neural Networks

Prediction of Physical Time Series Using Spiking Neural Networks . . . . . 816

David Reid, Abir Jaafar Hussain, Hissam Tawfik, and
Rozaida Ghazali

The Application of Artificial Immune Systems for the Prediction of

Premature Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 825
Rentian Huang, Hissam Tawfik, Abir Jaafar Hussain, and
Haya Al-Askar
 Table of Contents XXVII

Special Session on Computer Human Interaction

Using Multiple Visual Cues and Intelligent
Computing
Dynamic Hand Gesture Recognition Framework . . . . . . . . . . . . . . . . . . . . . 834
Prashan Premaratne, Shuai Yang, ZhengMao Zhou, and
Nalin Bandara

Special Session on Biometric System and Security

for Intelligent Computing
No-Reference Fingerprint Image Quality Assessment . . . . . . . . . . . . . . . . . . 846
Kamlesh Tiwari and Phalguni Gupta

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 855

 Affective Tutoring System for Android Mobiles

Ramón Zatarain-Cabada1, M.L. Barrón-Estrada1, José Luis Olivares Camacho1,

and Carlos A. Reyes-García2
1
Instituto Tecnológico de Culiacán, Juan de Dios Bátiz s/n, Col. Guadalupe,
Culiacán Sinaloa, 80220, México
2
Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)
Luis Enrique Erro No. 1, Sta. Ma. Tonanzintla, Puebla, 72840, México
{rzatarain,lbarron,jolivares}@itculiacan.edu.mx,
kargaxxi@inaoep.mx

Abstract. Detecting and responding to affective states may be more influential

than intelligence for tutoring success. This paper presents a software system
that recognizes emotions of users using Android Cell Phones. The system
software consists of a feature extractor, a neural network, and an intelligent
tutoring system. The tutoring system, the neural network, and the emotion
recognizer were implemented for running in Android devices. We also
incorporate a novel fuzzy system, which is part of the intelligent tutoring
system that takes actions depending of pedagogical and emotional states. The
recognition rate of the emotion classifier was 96 %.

Keywords: Intelligent Tutoring Systems, Affective Computing, Learning

Technologies, Artificial Neural Networks, Education.

1 Introduction
The rapid advancement of technology in recent decades has allowed imitate science
fiction since today there are computer systems that can recognize the emotional states
of people and still react to them with related actions.
Affective computing is a term coined by Rosalind Picard in 1995 [1] to define a
field of research that integrates different scientific disciplines, seeking to make
computers have the ability to behave intelligently, interacting naturally with users
through the ability to recognize, understand and express emotions. Knowing the
emotional state of a person provides relevant information about their psychological
state and gives a software system, the possibility to decide on how to respond to it.
Research in the area of affective computing aims to create systems to identify and
respond to the emotions of a user (e.g. a client). Emotions are detected by special
devices (pc camera, pc microphone, special mouse, neuro-headset, etc.) that can be
placed in a computer or a person [2]. These devices are responsible for picking up
signals (facial image, voice, mouse applied pressure, heart rate, stress level, etc.) of a
user and of sending them to the computer to be processed and then get the resulting

D.-S. Huang et al. (Eds.): ICIC 2014, LNAI 8589, pp. 1–10, 2014.
© Springer International Publishing Switzerland 2014
2 R. Zatarain-Cabada et al.

emotional state in real time. In the area of education, an affective system seeks to
change in an individual, a negative emotional state (e.g. confused) into a positive state
(e.g. committed), in order to facilitate an appropriate emotional state for learning.
An Intelligent Tutoring System (ITS) is a computer program that incorporates AI
techniques and pedagogy to provide tutors that know what they teach, who will teach
and how to teach [3]. An ITS goal is to provide tutoring services that support learning
[4]. Because the teaching-learning process is a complex area, ITS have support from
other areas of knowledge such as education, psychology and computer science, which
are combined to develop robust applications that are efficient tools for education. A
traditional Intelligent Tutoring System (ITS) reacts from a significant set of
pedagogical or cognitive strategies (i.e. a wrong answer or a help petition). The latest
related works on emotion recognition in ITS incorporates different methods
(hardware and software-based) to recognize student emotions [2, 5, 6, 7].
In this work, we present a system to incorporate emotion recognition to an ITS
running into a Mobile Device. We have integrated two methods for selecting the
learning style and emotional state of a student and to consider them in the ITS
response. For recognizing the learning style and the affective state, we implemented
two neural networks. During a training session, the first network (a SOM or Kohonen
network) used for detecting the learning styles, receives a number of different input
patterns (the student learning style obtained from an Inventory Learning Style
Questionnaire (ILSQ), the learning style of three defined courses, and the student’s
grade in each course), discovers significant features in these patterns and learns how
to classify the input patterns. The second network (a back-propagation neural
network), which is used to detect affective or emotional states, is trained with a
corpus of faces representing different emotional states. The affective and learning
style recognizers are used into a fuzzy system, which is part of an ITS.

2 System General Structure and Architecture

Figure 1 shows the general structure of the system software. We have an application
for Android devices, allowing the Intelligent Tutoring Systems accessed from mobile
devices, taking pictures that allow the extraction of facial features and determine the
student's emotion. The students will access the ITS through the web browser on a
device with Android operating system, which can be a Smartphone or Tablet with
Front Camera. The intelligent tutor requests the execution of the application for
extracting facial features, when necessary. The ITS request is through the web
browser, and is an invocation to the program installed on the mobile device, which
takes a picture to obtain features of the eyes and mouth which are submitted to the
ITS and then to a server with a neural network to determine the corresponding
emotion, providing such information to the Tutor. Once the emotion is obtained, the
ITS may take actions that allow students to improve their learning.
 Affective Tutoring System for Android Mobiles 3

Fig. 1. General Structure of the System Software

Figure 2 shows the conttext diagram of the system. The context diagram allowss us
to define the communicatiion that our system can have with other systems. In the
context diagram shown in Figure
F 2 we have the Android application with the systtem
that extracts facial featuress, which contains four components: Face, Right Eye, L Left
Eye and Mouth. The featurre extraction application communicates with the Intelliggent
Tutoring System, when ask ked taking pictures with the front camera of the device. T
The
Face component is responsible for finding the human face in the picture, using the
Haar-like features casccades method implemented in OpenCV librrary
(www.opencv.org). If the seearch is successful, the search for other objects (mouth, left
and right eyes) is performeed. Once the student's face is detected, we proceed to ffind
the components of the facee, which are the mouth, right eye and left eye. For optim mal
image processing, the searcch method ROI (Region of Interest) is used, which specifies
the regions of interest in which
w you want to search, discarding the rest of the imaage.
Once found the objects in i the image, a set of transformations are perform med,
facilitating the search for object edges to calculate distances opening (mouth and
eyes). This data (the distan nces) is provided to a neural network for classificationn of
emotions.
The ITS has three com mponents like a traditional ITS: the domain module whhich
holds all knowledge of the area or field, which in our case is in the area of basic m
math
for elementary level. Th he student module has the student knowledge (baasic,
intermediate or advanced leevel) of the student. A diagnostic test determines the leevel
of the student. The tutor mo odule defines the next exercise to be solved by the student.
To do this, the ITS uses their pedagogical results (e.g. the time taken to solvve a
problem) and their affectiv ve or emotional state. For reaching this decision, the tuutor
uses an emotion recognizeer and an affective module which in turn use an artificial
neural network and a fuzzy system.
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by the way, five-year-old children were able to do in the days of
Cicero. Others soar in thoughts in the sky, and are ignorant of what
goes on upon earth. Others again are strong in artificial logic, having
an extreme absence of natural logic. In short, Leipsic proves beyond
controversy that learning does not beget common sense. I left these
pedants, and went to Frankfurt-on-the-Main. This city is celebrated
for its antiquities, and is noteworthy from the fact that the Roman
Emperor is chosen here. I was in the election room from which he
issues to the people. But its antiquity consists merely in being old: all
I saw there were four empty walls in an old building. They showed
me also the famous so-called La Bulle d’Or of Emperor Charles IV.,
which was written in the year 1356, and I was also in the Imperial
Archives. But it was hardly worth my while to climb up garrets and
down cellars, in order to see the relics of a rude age. From Frankfurt
I travelled through German principalities: every step a new
principality. I saw Hanau, Mainz, Fulda, Sachsen-Gotha, Eisenach
and a few other principalities of minor princes. I found the roads
frequently not paved, but I had nevertheless to pay dearly for the
pavement. When they pulled me out of a bog and asked pavement
money of me, I had the courage to ask them: “Where is it?” To which
they answered me that his Majesty, the reigning prince, had the
intention of having the roads paved, but that at the present he was
only collecting toll. Such justice in regard to strangers has led me to
make my own conclusions in regard to their relations with their
subjects, and I did not at all wonder when from every hut there came
out a crowd of beggars and followed my carriage....
From here I went into France, and reached the famous city of
Lyons. In this country the roads are very good; but in the cities the
streets are so narrow and are so badly kept that I cannot understand
how people with their five senses manage to live in such dirt. It is
evident that the police does not interfere with it. To prove this I shall
take the liberty of telling your Highness an occurrence. I was walking
in the finest and largest street in Lyons (which, however, cannot
compare with our by-streets), and saw in bright daylight burning
torches and a crowd of people in the middle of the street. Being
near-sighted, I naturally thought it was some elegant funeral. Upon
approaching nearer out of curiosity, I saw how great my mistake
was: Messrs. Frenchmen had simply stuck a pig and were singeing it
in the middle of the street! The stench, dirt and a crowd of leisure
people who were watching the operation compelled me to take
another street. I have not yet seen Paris, so I do not know whether
my olfactories will suffer there less; in any case, all the French cities
which I have so far seen are badly off as to their cleanliness.
Paris, March 20 (31), 1778.
... Voltaire’s arrival in Paris produced the same effect on the
people here as if a divinity had come down upon earth. The respect
shown to him in no way differs from worship. I am confident that if his
deep old age and ailments did not oppress him, and he wished to
preach now some new sect, the whole nation would at once turn to
him. Your Excellency will form your own opinion from what follows
whether one can come to any other conclusion from the reception
the public gave him.
When he arrived here, the poets who are devoted to him began to
write poems in his honour, while those who hate him sent him
anonymous satires. The first are printed, but not the other, for the
Government has by a special rescript forbidden to print anything that
might be prejudicial to Voltaire. This consideration is shown him as
much for his great talents as for his advanced age. This man of
eighty-five years has composed a new tragedy, Irene and Alexis
Comnenus, which has been performed. Although it can by no means
be compared to his former plays, yet the public received it with
rapture. The author being ill, he was not present at the first
presentation. It is only the first time yesterday that he has driven out:
he was in the Academy, then in the theatre, where they purposely
gave his new tragedy.
As he drove out from his house, the carriage was accompanied as
far as the Academy by an endless throng of people who kept up
applauding. All the academicians came out to meet him. He was
seated in the president’s chair and, waiving the customary voting,
was elected by acclamation to be president for the April quarter. As
he walked down the staircase and took his seat in the carriage, the
populace demanded vociferously to take off hats. From the Academy
to the theatre he was accompanied by the people’s cheering. When
he entered his box, the audience applauded repeatedly with
indescribable rapture, and a few minutes later the oldest actor,
Brisard, stepped into his box with a wreath which he placed on
Voltaire’s head. Voltaire immediately took the wreath off and with
tears of joy spoke aloud to Brisard: “Ah, Dieu! vous voulez donc me
faire mourir!” The tragedy was played with much greater perfection
than at any previous performance. At its conclusion there was a new
spectacle. All the actors and actresses surrounded Voltaire’s bust
and adorned it with laurel wreaths. This homage was followed by the
people’s applause, which lasted nearly fifteen minutes. Then
Madame Vestrice, who had played Irene, turned towards Voltaire
and read some laudatory verses. To show their appreciation, the
public demanded that the verses be read again, and they applauded
wildly. As soon as Voltaire seated himself in his carriage, the people
stopped the coachman and cried: “Des flambeaux, des flambeaux!”
When the torches were brought, they ordered the coachman to drive
at a slow pace, and an endless crowd accompanied him to his very
house with torches, crying all the time: “Vive Voltaire!” Voltaire has
received many an ovation in his lifetime, but yesterday was, no
doubt, the best day of his life, which, however, will soon come to an
end. Your Excellency will see how he now looks from his portrait
which I here enclose and which is a very good likeness of him.
 Ermíl Ivánovich Kostróv. (1750-1796.)
Kostróv was the son of a peasant. He studied in a seminary
and began to write verses early, first under the influence of
Lomonósov, in the pseudo-classic style,—later, under the
influence of Derzhávin, he cultivated a simpler and better
language. His chief services to Russian literature are his
translations of Apuleius, Ossian, and the Iliad. The ode which
is given here marks the turning-point in his manner of writing,
and at the same time indicates how great was the change
brought about by Derzhávin’s Felítsa (see p. 378) in Russian
poetry.

LETTER TO THE CREATOR OF THE ODE IN PRAISE OF

“FELÍTSA, THE KIRGÍZ-KAYSÁK PRINCESS”

Singer, to whom with a gentle smile the Muse has lately brought
from the Parnassian heights a wreath, I hanker for your friendship
and union with you. Moscow is my habitation, you sing the Neva
stream. But not the distant roads, nor mounts, nor hills, nor forests,
nor rivers shall impede my zeal to you, which to Petropolis shall be
borne, to issue in your breast and ears: not impossible to Muses is
what the Muses will.
Tell me, I pray, how without a lyre, nor violin, not even having
saddled the Parnassian steed, you have sung so sweetly Felítsa’s
acts, and her crown’s life-giving beams? You evidently have walked
all streets and byways on Pindus’ heights and in the grassy vale of
the pure Muses, and to glorify, console, make happy, amuse the
Princess, you have discovered a new, untrodden path. Having
discovered it, you ran it at will, and neither stump nor stone e’er
tripped you, but all appeared to you a grassy mead, and your caftan
was nowhere rent by thorns. Proclaiming the praises of the Princess,
recounting the pleasures of the bashaws, you played the bagpipe,
yet sang enticingly withal.
 Disdaining the evil conscience of the envious, you onward bore,
which boldness seeing, Parnassus wound a wreath for you. Their
flowing hair descending on their arms, disporting on their pink-white
breasts and cheeks, the forms of fairy nymphs from the Neva rose;
gently waving on the crests, they listened intent to you, and praised
the beautiful innovation of your verse. In token of their heartfelt
tribute, they clapped their hands in ecstasy, then disappeared into
the crystal depths.
By easy post Felítsa’s praise was borne to Moscow, to the delight
of all the hearts, and all who read have sung your praise, and
arbiters of taste have wound a wreath for you. They have read it a
hundred times, yet listen gladly, with attention, when someone in
their presence reads it again, and cannot assuage their spirits, nor
satisfy their captive ears, while listening to its sportive jests. Just so
a garden, with charming shrubs and shade of trees, planted on a hill
above a stream of limpid waters, though it be well known to us,
though known the taste of every fruit therein, though familiar to us its
every path, yet drawn by a mysterious feeling, we hasten to walk in it
once more, and turn our glances all about us, to discover something
new, though we have seen it all before.
Our ears are almost deaf from the vociferous lyric tones, and,
meseems, ’tis time to come down from the clouds, lest, forgetful of
the law of equilibrium, and flying from the heights, one break his
arms and legs: no matter what our endeavour be to rise on high,
Felítsa’s deeds will still be higher. She likes simplicity of style, so ’t
were better, treading that road in modesty, to raise our voice to her.
Dwelling on Parnassus in union with the nymphs, I have thrummed
the sonorous harp, while praising the Kirgíz-Kaysák Princess, and
have only earned cold praises. All lauded there my verses, flattered
me, though themselves were but amused; and now they have the
honour in oblivion to lie: ’tis evident high-soaring odes are out of
fashion.
Above us you have risen through your simplicity! Write, as
formerly, again a letter to your neighbour; you have well depicted his
luxurious mind, how he invites a hungry mob to dinner, games and
luxuries on the tables; or, loving Nature’s beauties, sing of the crystal
waters, as once you sang the Spring of Grébenev. This spring,
flowing through the valley, even now is pleasing to me: whenever I
slaked my thirst, a ray of joy shone to me.
But to you, who preside most wisely, leader of the Muses, their
labours’ judge, listening to their sweet thunderous music, to you this
honour and praise is due, because, burning with zeal and inventive
of new paths, you labour to advance our native tongue. It is majestic,
sweet and rich, thunderous, elate, liquid and strong, and great is
your work of its perfection. Encouraged by you, the lovers of the
sciences have with heartfelt zeal walked on the glorious path: we
see the fair Russian diction in their labours, and its progress in him
who has extolled you.
I shall say it without hesitation: you emulate Minerva, and bring
your rest as a sacrifice to the Muses, and the glory of your country is
your pleasure and consolation. Your exploits are enviable to men.
With Felítsa’s beloved, precious name, with Felítsa’s praise and the
laudation of her wise acts the beginning of these labours has been
adorned, and has brought joy and rapture to its readers. Blessed is
that beginning where her resplendent name appears, and the end is
crowned with success. To him who thus has glorified Felítsa, and
has given a new flavour to his verses, honour and glory from the
depth of our hearts!
Alexander Nikoláevich Radíshchev. (1749-1802.)
In 1765 Catherine II. sent twelve young men to Leipsic to
be educated in the University; among the number was
Radíshchev. He studied philosophy under Platner, and for his
own amusement took a full course in medicine. Upon his
return he was attached to the Kommerz-Kolleg, a kind of
Department of Finance, where he distinguished himself for his
unexampled honesty and gained the love of its President,
Count Vorontsóv, whom he had the courage to oppose in a
decision at law, in order to save some innocent men from
transportation to Siberia. When he was later put in charge of
the Customs House of St. Petersburg, he discovered that the
considerable traffic with England demanded a knowledge of
English, if he wished to dispense with a translator; accordingly
at the age of thirty he acquired the English language and
began to read its literature, which exerted a great influence
upon him.
In 1790 he wrote his Journey from St. Petersburg to
Moscow, which he distributed among his friends, though it
had not been approved by the censor. This work, written in
the style of Sterne’s Sentimental Journey, is not only
remarkable as a piece of literature, but also as a political
pamphlet. It attacks the institution of Russia in the light of the
most advanced liberalism of France and North America.
Radíshchev advocated in no unmistakable terms the
liberation of the serfs, almost half a century before Turgénev.
When Catherine II. read the book, she exclaimed: “He is a
Martinist. He is worse than Pugachév, he praises Franklin.”
Radíshchev was banished to Siberia. There he devoted
himself to literature, wrote his Ode to Liberty, which is the
forerunner of all the poems of liberty by Rylyéev, Ogarév,
Odoévski, and a few longer poems in a lighter vein. Emperor
Paul pardoned him, and Emperor Alexander advanced him to
higher honours. When an acquaintance of his accused him of
 returning to his youthful ideals and warned him of subjecting
himself to the danger of another banishment, he committed
suicide in a moment of despondency.

JOURNEY FROM ST. PETERSBURG TO MOSCOW

DEPARTURE

After having taken supper with my friends, I took my seat in the

kibítka. The driver drove the horses at full gallop, as was his wont,
and in a few minutes we were outside the city. It is hard to part, even
for a short time, from those who have become necessary to us at
every moment of our existence. It is hard to part,—but happy is he
who can part without smiling, for love or friendship is his consolation.
You weep as you say “good-bye”; but think of your return,—and let
your tears dry up at this thought, as dries up the dew before the face
of the sun. Happy is he who weeps, hoping to be consoled! Happy is
he who sometimes lives in the future! Happy is he who lives in
meditation! His existence is enriched; his joy is multiplied, and calm
assuages the gloom of his pining, generating images of happiness in
the mirrors of his contemplation.
I lay in the kibítka. The tinkling of the post bell was monotonous to
my ears, and finally brought to me beneficent Morpheus. The grief of
my parting persecuted me in my deathlike state, and painted me to
my imagination as forlorn. I saw myself in a spacious vale which had
lost all its amenity and greenness of leafage through the hot rays of
the sun. There was not a spring to offer coolness, nor tree-shade to
protect from the heat. I was a hermit, left in the midst of Nature! I
shuddered. “Miserable man!” I sighed, “where are you? What has
become of all that has enticed you? Where is all that has made your
life agreeable? Is it possible that the pleasures which you have
tasted are only an idle dream?”
Luckily there was a deep rut in the road, and my kibítka, getting
into it, jostled me and woke me up. The kibítka stopped. I raised my
head and saw three habitations in a barren spot.
 “What is that?” I asked my driver.
“A post station.”
“Where are we?”
“In Sofíya,” and he unhitched the horses.

SOFÍYA

All around me was silence. I was absorbed in contemplation and

did not notice that the kibítka had been standing quite a while without
the horses. My driver broke my meditation:
“Master, father, some money for a drink!”
This tax is illegal, but no one objects to paying it, in order that he
may be able to travel at his ease; the twenty kopeks I gave him were
a good investment. Who has travelled by post knows that a passport
is a precaution without which any purse, unless it be a general’s, will
have to suffer. I took it out of my pocket and went with it, as people
sometimes go with the cross for their defence.
I found the Post Commissary snoring. I touched his shoulder.
“Whom does the devil drive so? What a miserable habit to depart
from the city at night? There are no horses here,—it’s too early yet.
Go into the inn and drink tea, or go to sleep!”
Having said that, the Commissary turned to the wall, and went to
snoring again. What was I to do? I once more shook the
Commissary by his shoulder.
“What is the matter with you? I told you there are no horses!” and,
covering himself with the blanket, the Commissary turned away from
me.
If the horses are all engaged, I thought to myself, then it is not
right for me to disturb the Commissary’s sleep. But if there are any
horses in the stable ... I made up my mind I would find out whether
the Commissary told the truth. I went into the yard, hunted up the
stable and found some twenty horses in it. It is true, one could count
the bones on them, yet they would have taken me to the next station.
From the stable I returned to the Commissary, and shook him harder
than before, for I felt I had a right to do so, having discovered that he
had told a lie. He jumped up from his bed and without opening his
eyes asked who had arrived. “I ...” But coming to his senses, and
noticing me, he said:
“Young man, you are evidently in the habit of commanding drivers
of olden days, when they used to beat them with sticks. Well, that
won’t work now-a-days.” The Commissary lay down angrily in his
bed again. I had really a desire to treat him like one of those drivers
when they were discovered cheating; but my generosity to the city
driver caused the Sofíya drivers to hurry up and hitch the horses to
the kibítka. Just as I was getting ready to commit a crime on the
back of the Commissary, the bells were heard in the yard. I remained
a good citizen, and thus twenty kopeks saved a peaceable man from
an inquest, my children from an example of incontinence in anger,
and I discovered that reason is a slave to impatience.
The horses carried me away. The driver started a song which, as
usual, was a doleful one. He who knows the tunes of Russian
popular songs will admit that there is something in them that speaks
of sadness of spirit. Nearly all the tunes of such songs are in the
minor key. In this musical inclination of the popular ear one may find
a solution of the trend of his actions. In it one may discover the
condition of the nation’s soul. Look at a Russian! You will always find
him lost in meditation. If he wants to drive away ennui, or, as he calls
it, have a good time, he goes to the inn. In his intoxication he is
impulsive, bold, quarrelsome. If anything takes place not to his liking,
he at once starts a brawl or fight. A churl who goes into the inn with a
downcast look and returns from it covered with blood from having
had his ears boxed may throw a light on many an enigmatic point in
Russian history.
My driver was singing. It was three o’clock in the morning. As
before the bell, so now his song put me to sleep: “O Nature! Having
swathed man at his birth in the winding-sheets of sorrow, dragging
him all his life over the forbidding crags of fear, ennui and sadness,
you have given him sleep as a consolation. You fall asleep, and all is
at an end! Unbearable is the awakening to the unfortunate man. Oh,
how acceptable death is to him! And if it is the end of sorrow.... All-
kind Father! Wilt Thou turn away Thy look from him who ends his life
in a manly way? To Thee, the source of all goodness, this sacrifice is
brought. Thou alone givest strength when creation trembles and is
convulsed. It is the voice of the Father, calling His child unto Himself!
Thou hast given me life, to Thee I return it: upon earth it has become
useless.”

TOSNÁ

When I left St. Petersburg I thought I would find a very good road.
All those who have travelled upon it after the Emperor have thought
so. It had been such, indeed, but only for a short time. The dirt which
had been put upon the road in dry weather in order to make it even
had been washed by the rains, forming a swamp in the summer, and
made it impassable. Fearing bad weather, I got out of the kibítka and
went into the post station, intending to take a rest. In the room I
found a traveller who was sitting behind a long, common peasant
table in the nearer corner and was turning over some papers. He
asked the Post Commissary to give him horses as soon as possible.
To my question who he was, I learned that he was a pettifogger of
the old style, and that he was going to St. Petersburg with a stack of
torn papers which he was then examining. I immediately entered into
a conversation with him, and here is what he said:
“Dear sir,—I, your humble servant, have been a Registrar in the
Archives of the Estates, where I had an opportunity to make good
use of my position: by assiduous labour I have collected a
genealogy, based on clear documentary proof, of many Russian
families, and I can trace their princely or noble origin several
centuries back. I can reinstate many a man in his princely dignity, by
showing his origin from Vladímir Monomákh, or even from Rúrik.
Dear sir,” he continued, as he pointed to his papers, “all Great-
Russian nobles ought to purchase my work, paying for it more than
for any other wares. But with the leave of your High Birth, Noble
Birth, or High and Noble Birth, for I do not know how to honour you,
they do not know what they need. You know how the orthodox Tsar
Feódor Aleksyéevich of blessed memory has injured the Russian
nobility by doing away with the prefecture. That severe legislation
placed many honourable princely and royal families on a level with
the Nóvgorod nobility. But the orthodox Emperor Peter the Great has
entirely put them in the shade by his Table of Ranks. He opened the
way to all for obtaining the title of nobility through military and civil
service, and he, so to say, has trampled the old nobility in the dirt.
Our Most Gracious Mother, now reigning, has confirmed the former
decrees by her august Law of the Nobility, which has very much
disquieted all our higher nobles, for the old families are placed in the
Book of the Nobility lower than the rest. There is, however, a rumour
that there will soon be issued a supplementary decree by which
those families that can trace their noble origin two or three hundred
years back will be granted the title of Marquis or something like it, so
that they will have some distinguishing feature from the other
families. For this reason, dear sir, my work must be acceptable to all
the old nobility. But there are rascals everywhere. In Moscow I fell in
with a company of young gentlemen to whom I proposed my work, in
order to be repaid through their kindness at least for the paper and
ink wasted upon it. But instead of kindness they heaped raillery upon
me; so I left that capital from grief, and am on my way to St.
Petersburg, where there is more culture.”
Saying this, he made a deep bow, and straightening himself up,
stood before me with the greatest respect. I understood his thought,
took something out of my purse and, giving it to him, advised him to
sell his paper by weight to peddlers for wrapping paper, for the
prospective marquisates would only turn people’s heads, and he
would be the cause of a recrudescence of an evil, now passed in
Russia, of boasting of old genealogies.

LYUBÁNI

I suppose it is all the same to you, whether I travelled in summer

or winter, especially since it is not uncommon for travellers to travel
both summer and winter, starting out in a sleigh and returning in a
wheel carriage. The corduroy road wore out my sides. I crawled out
of the kibítka, and started on foot. While I was lying in the kibítka, my
thoughts were directed to the immeasurableness of the world, and
while my soul flitted away from the earth, it seemed easier to bear
the jostling of the carriage. But spiritual exercises do not always
distract our corporeality, and it was in order to save my sides that I
went on foot.
A few steps from the road I noticed a peasant who was ploughing
his field. It was warm; I looked at my watch: it was twenty minutes to
one. I left the city on Saturday, so it was Sunday then. The peasant
that was ploughing evidently belonged to a landowner that did not
receive any tax from him. The peasant was ploughing with great
care; evidently the field did not belong to the master. He was turning
the plough with remarkable ease.
“God aid you!” I said as I approached the ploughman, who did not
stop but finished the furrow he had begun.
“God aid you!” I repeated.
“Thank you, sir!” said the ploughman as he cleaned the
ploughshare and transferred the plough to a new furrow.
“You are, of course, a dissenter, since you work on Sunday.”
“No, sir, I make the correct sign of the cross,” he said, and showed
me his three fingers put together; “but God is merciful and does not
want a person to starve, as long as he has a family and sufficient
strength.”
“Have you not any time to work during the week, that you work on
a Sunday, and at that in a great heat?”
“In the week, sir, there are six days, and we have to work for the
manor six times a week, and in the evening we haul the hay from the
meadows, if the weather is good; and on holidays the women and
girls go to the woods to gather mushrooms and berries. God grant a
rain this evening,” he added as he made the sign of the cross. “Sir, if
you have any peasants, they are praying for the same.”
 “I have no peasants, my friend; and so nobody curses me. Have
you a large family?”
“Three sons and three daughters. My eldest is ten years old.”
“How do you manage to get enough grain, if you have only the
Sundays to yourself?”
“Not only the Sundays,—the nights are ours too. We need not
starve, if we are not lazy. You see, one horse is resting; and when
this one gets tired, I’ll take the other, and that’s the way I make my
work count.”
“Do you work the same way for your master?”
“No, sir! It would be sinful to work the same way; he has in his
fields one hundred hands for one mouth, and I have but two hands
for seven mouths, if you count it up. If you were to work yourself to
death at your master’s work, he would not thank you for it. The
master will not pay the capitation tax; he will let you have no mutton,
no hempen cloth, no chicken, no butter. Our people are fortunate in
those places where the master receives a rent from the peasant,
particularly without a superintendent! It is true, some good masters
ask more than three roubles for each soul, yet that is better than
tenant labour. They are now getting in the habit of letting farms out to
renters who, being poor, flay us alive. They do not give us our own
time, and do not let us go out in the winter to work for ourselves,
because they pay our capitation tax. It is a devilish idea to let one’s
peasants do work for somebody else! There is at least a chance of
complaining against a superintendent, but to whom is one to
complain against a tenant?”
“My friend! You are mistaken: the laws do not permit to torture
people.”
“Torture, yes! But, sir, you would not want to be in my hide!” In the
meantime the ploughman hitched another horse to his plough and,
bidding me good-bye, began a new furrow.
The conversation with this agriculturist awakened a multitude of
thoughts in me. Above all, I thought of the inequality of the peasant’s
condition. I compared the crown peasants with those of the
proprietors. Both live in villages, but while the first pay a stated tax,
the others have to be ready to pay whatever the master wishes. The
first are judged by their peers; the others are dead to the laws,
except in criminal matters. A member of society only then is taken
cognisance of by the Government that protects him when he violates
the social bond, when he becomes a criminal! That thought made all
my blood boil. Beware, cruel proprietor! On the brow of every one of
your peasants I see your condemnation!
Absorbed in these thoughts I accidentally turned my eyes to my
servant, who was sitting in front of me in the kibítka and was shaking
from side to side. I felt a sudden darkness come over me, which
passed through all my blood and drove a burning feeling upwards
and made it spread over my face. I felt so heartily ashamed of
myself, that I wanted to cry. “In your anger,” I said to myself, “you
attack the cruel master who maltreats his peasants in the field; and
are you not doing the same, or even worse? What crime did your
poor Petrúshka commit that you do not allow him to enjoy the
comfort of our misfortunes, the greatest gift of Nature to the
unfortunate man,—sleep? ‘He receives his pay, his food and dress; I
never have him whipped with a scourge or sticks.’ O you kind man!
You think that a piece of bread and a rag give you the right to treat a
being that resembles you as a top? You are merely boasting that you
do not very often whip it as it is whirling about. Do you know what is
written in the first law of each man’s heart? ‘If I strike anyone, he has
the right to strike me also.’ Remember the day when Petrúshka was
drunk and did not dress you fast enough! Remember how you boxed
his ears! Oh, if he had then, drunk as he was, come to his senses,
and had answered your question in a befitting manner! Who has
given you the right over him? The law! Law! And you dare besmirch
that sacred name! Wretch!...” Tears flowed from my eyes, and in this
condition the post horses brought me to the next station.
 Alexander Onisímovich Ablesímov. (1742-1783.)
Ablesímov was a frequent contributor to several periodical
publications; his contributions present no special interest, but
he gained a great reputation by his comic opera The Miller,
which, though it is an imitation of a foreign original, was the
first play to introduce a popular element, taken directly from
the life of the people. The public hailed this comedy as a new
departure; it was given to crowded houses twenty-seven
times in succession, and a number of imitations appeared
with the same element of sorcery and country life for their
background.

THE MILLER

ACT I

The stage represents on one side a forest, with small villages in

the distant hills, and on the other a mill, and nearby a waggon with
sacks. In front of it is a tree.

SCENE 1

Miller (alone. He is planing a board and sings, only the song is

without words and music. Then he says): What song is that?... Oh,
yes: “How our night from midnight” ... that’s it ... (he begins to sing
that tune, continuing his work).

How our night from midnight,

From midnight to white day ...

What a downpour it has been, and now it has stopped! (He sings
again, and continues his song.)
 ’Twas at the dawn, the early one,
At the fall of the shining moon....

How it did blow! I declare, it did blow; why, it almost tore my mill
down. I would have been left with nothing. It has done some
damage,—thanks to the Lord, not much damage. Did I say not much
damage? Well, I have enough to do to fix it up. (Putting the level to
the board.) It’ll come out all right, and all will go well again.
(Advancing towards the orchestra.) I have to laugh every time I think
of it; they say that a mill cannot exist without a wizard, and that a
miller isn’t just a man like anybody else: he is on speaking terms with
the house-spirit, and the house-spirits live in their mills like devils ...
ha, ha, ha, ha! What bosh! Am I not a miller through and through? I
was born, brought up, and have grown old in the mill, and yet I have
never laid my eyes on a house-spirit. Now, to tell the gospel truth, it’s
just this: if you are a shrewd fellow and a good hand at cheating, that
sorcery business is a good thing.... Let them prattle what they
please, but we earn our bread by our profession.

Who by cheating makes a living,

Him at once all call a gipsy,
And you gain through gipsy dealings
The reputation of a wizard.
Even in that way the witches
Make a living by deception.
There’s a big lot of these rascals:
Some of them bespeak the water,
Others turn the sieve for people,
And through such tricks make a living!
Just like me, sinful man!...

SCENE 2. FILIMÓN AND THE FORMER

Miller (noticing him). Ah! I am getting a guest. I’ll earn a penny this
day. (To Filimón.) Godspeed, young man!
 Filimón. My respects, old man.
Miller. Whence come you, whither tend you?
Filimón. Not farther than my business takes me.
Miller. Of your own will, or by compulsion?
Filimón. I am looking for horses: my roan and grey have gotten
away from me; they are fine horses, such fine horses. (Aside.) He is
a fortune-teller: I’ll try my fortune with him. (To the Miller.) Say, old
man, I want to ask you——
Miller. What is it you want? As you please, I am at your service.
Filimón. That’s good! And I’ll pay you for it. Tell me my fortune:
shall I find my horses?
Miller. Shall you find your horses?
Filimón. That’s it, old man. I am very anxious to find out about
them.
Miller. Now, how about that; is there going to be anything?
(Stretches out his hand to him.)
Filimón. First tell me, old man, and then we’ll see.
Miller (turns away from him, and angrily begins a song):

Tell the fortune:

As the guess is,
So is the pay.

Filimón. But, old man, I expect to pay you.

Miller.

’Tis with a promise

As with a chair:
If you sit and do not eat,
Then your belly is not full.
 Filimón. Believe me, I am not lying to you.
Miller.

If it’s so,
All this talking is in vain;
Take out your purse,
Don’t talk uselessly,
Count out the money.
(Puts out his hand, and looks in his eyes.)

Filimón. Well, I don’t care: I’ll give you some money in advance.
Miller. Only this?
Filimón. It will do for the present; what more do you want?
Miller (aside). You won’t get off with less than half a rouble.
Filimón. What are you going to tell me now?
Miller. What is it now, early in the morning?
Filimón. Not very late yet, the sun has not yet set behind the
woods.
Miller. Turn three times around, towards the sun.
Filimón. What for?
Miller. That’s what I need in my sorcery. Do as you are told!
Filimón. To please you, I’ll turn around. (Turns around once.)
Miller. Once more, towards the sun.
Filimón (turning around). Here it is, and towards the sun.
Miller. Now stand against this tree. (Filimón is about to start for the
tree, but the Miller says): No, no, stop! Have you a kerchief?
Filimón (taking out his handkerchief). Here it is.
 Miller. Close your eyes tight, and tie your kerchief over them.
That’s all right! Now listen: you must stand quiet, and don’t move
from the spot, nor speak a word to anyone, while I go and see the
elder.
Filimón (does all the Miller commands him to do). But suppose
someone should come and ask me why I am standing there, and
why my eyes are tied up?
Miller. Not a word to anybody; but you may grumble to yourself.
Filimón. May I sing a song?
Miller. You will frighten all. No, you must not.
Filimón (aside). What is it all going to be?
Miller. Stand still and don’t move!