Soft Computing in Machine Learning

120 Pages·2014·10.783 MB·English

by  Sang-Yong Rhee, Jooyoung Park, Atsushi Inoue (eds.)

Advances in Intelligent Systems and Computing 273
Sang-Yong Rhee
Jooyoung Park
Atsushi Inoue Editors
Soft Computing
in Machine Learning
Advances in Intelligent Systems and Computing
Volume 273
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·
Sang-Yong Rhee Jooyoung Park
Atsushi Inoue
Editors
Soft Computing
in Machine Learning
ABC
Editors
Sang-YongRhee AtsushiInoue
KyungnamUniversity EasternWashingtonUniversity
Gyeongnam Washington
Korea USA
JooyoungPark
KoreaUniversity
Seojong
Korea
ISSN2194-5357 ISSN2194-5365 (electronic)
ISBN978-3-319-05532-9 ISBN978-3-319-05533-6 (eBook)
DOI10.1007/978-3-319-05533-6
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014933545
(cid:2)c SpringerInternationalPublishingSwitzerland2014
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Preface
As users or consumers are now demanding smarter devices, intelligent systems
are revolutionizing by utilizing machine learning. Machine learning as part of
intelligent systems is already one of the most critical components in everyday
tools ranging from searchengines and credit card fraud detection to stock mar-
ket analysis. You can train machines to perform some things, so that they can
automatically detect, diagnose, and solve a variety of problems. The intelligent
systems have made rapid progress in developing the state of the art in machine
learningbasedonsmartanddeepperception.Usingmachinelearning,theintelli-
gentsystemsmakewidelyapplicationsinautomatedspeechrecognition,natural
language processing, medical diagnosis, bioinformatics, and robot locomotion.
This book aims at introducing how to treat a substantial amount of data, to
teach machines and to improve decision making models. And this book special-
izesinthe developmentsofadvancedintelligentsystemsthroughmachinelearn-
ing. It consists of 11 contributions that features illumination change detection,
generator of electronic educational publications, intelligent call triage system,
recognitionof rocksat uranium deposits, graphics processingunits, mathemati-
cal model ofhit phenomena, selectionandmutationin geneticalgorithm,hands
and arms motion estimation, application of wavelet network, Kanizsa triangle
illusion, and support vector machine regression. Also, it describes how to apply
themachinelearningfortheintelligentsystems.Thiseditionispublishedinorig-
inal, peer reviewedcontributions coveringfrominitial designto final prototypes
and verifications.
Tohelpreadersunderstandarticles,wedescribetheshortintroductionofeach
article as follows;
1.“Sudden Illumination Change Detection and Image Contrast Enhancement”:
This paper introduces a new method for detecting sudden illumination change
efficiently in real time by using local region information and fuzzy logic. Also it
proposesanautomaticparameterselectionmethodforcontrastlimitedadaptive
histogram equalization method by using entropy of image and adaptive neural
fuzzy inference system.
VI Preface
2. “Frame concept for generator of electronic educational publications”: This
paper describes a system of methods to create the generator of Electronic Edu-
cationalPublications(EEP)forhighereducationoncrediteducationtechnology,
in order to automate a process of EEP.
3. “Intelligent call triage system with algorithm combining decision-tree and
SVM”: This article proposes a new online learning algorithm that constructs a
subspace with a decision tree for a call triage support system. This algorithm
can build a subspace with a decision tree for learning an increasing number of
call triage records online.
4.“Recognition of Rocks at Uranium Deposits by Using a Few Methods of Ma-
chineLearning”:ForuraniumextractioninKazakhstan,thispaperproposes“ad-
jacencycube”methodfor integrationofresultsoffew interpretationalgorithms.
Data interpretation can be performed using learned systems, such as artificial
neural network (ANN), Linear Discriminant Analysis Classifier (LDAC), Sup-
port Vector Classification (SVM), k-Nearest-Neighbor(k-NN) and etc.
5.“MoreFasterSelf-OrganizingMapsby GeneralPurposeonGraphicsProcess-
ing Units”: As there are many loops which are simple calculationin learning al-
gorithmofSOM,thispaperdescribesabenefitofGPGPUtoacceleratelearning
of Self-Organizing Maps(SOM). GPGPU feature an acceleration of the specific
use computation and an adequtability for acceleration of simply calculation of
loop iteration.
6.“AnalysisofLocalConcertsusingFacebookAdaptingtheMathematicalModel
of Hit Phenomena”: This paper presents a mathematical model for the hit phe-
nomenoninentertainmentwithinasocietyasastochasticprocessofinteractions
of human dynamics. This model can be applicable to Japanese motion picture
market or numbers of Facebook viewers.
7.“EffectiveSelection and Mutation in Genetic Algorithm for PAPR Reduction
of OFDM Signal”:This paper proposesan improvedgenetic algorithm(GA) for
the PAPR reduction based on tone injection (TI). The effectiveness of the GA
method is demonstrated by numerical simulations in terms of PAPR, computa-
tion time and bit error rate (BER).
8.“Hands and arms motion estimation of a car driver with depth image sensor
byusingparticlefilter”:Thispaperproposestoincorporatesomeparticlesinten-
tionally switching the left and the right of the hands in a framework of particle
filter. This idea can reduce the mistaken (opposite) determination of left and
right and will increase the opportunity to recover automatically from the oppo-
site determination.
9. “SNR Improvement of an Optical Wave Microphone Using a Wavelet Net-
work”: As the optical wave microphone can detect the sound without making
any contact with others, the authors adopted wavelet network as information
processing. This paper verifies a noise reduction at low frequency using only
proposed algorithm.
10.“Originof Kanizsa triangle illusion”: This paper introduces Kanizsa triangle
figuresequippedwithstripenotchesonitsinducerstoexperimentalparticipants.
Preface VII
The research concludes considering the mechanism of Kanizsa triangle illusion
for global functional property.
11.“LTS-SVMR for Modeling of Nonlinear Systems with Noise and Outliers”:
This article proposes the least trimmed squares support vector machine regres-
sion(LTS-SVMR)whichisthe hybridoftheleasttrimmedsquares(LTS). LTS-
SVMR can effectively remove large noise and outliers under the proper initial
nonlinear function and ensure robust performance.
Wewouldappreciateitifreaderscouldgetusefulinformationfromthearticles
and contribute to creating innovative and novel concept or theory. Thank you.
Sang-Yong Rhee
Jooyoung Park
Atsushi Inoue
Contents
Sudden Illumination Change Detection and Image Contrast
Enhancement................................................... 1
Bayanmunkh Odgerel, Chang Hoon Lee
Frame Concept for Generator of Electronic Educational
Publications .................................................... 11
Altynbek Sharipbay, Assel Omarbekova, Alma Zakirova
Intelligent Call Triage System with Algorithm Combining
Decision-Tree and SVM ........................................ 21
Kento Yokose, Tomoki Hamagami
Recognition of Rocks at Uranium Deposits by Using a Few
Methods of Machine Learning .................................. 33
E. Amirgaliev, Z. Isabaev, S. Iskakov, Y. Kuchin, R. Muhamediyev,
E. Muhamedyeva, K. Yakunin
More Faster Self-Organizing Maps by General Purpose on
Graphics Processing Units...................................... 41
Shinji Kawakami, Keiji Kamei
Analysis of Local Concerts Using Facebook Adapting the
Mathematical Model of Hit Phenomena ........................ 53
Yasuko Kawahata, Etsuo Genda, Chinami Hara, Akira Ishii
Effective Selection and Mutation in Genetic Algorithm for
PAPR Reduction of OFDM Signal.............................. 61
Noritaka Shigei, Kentaro Araki, Hiromi Miyajima
Hands and Arms Motion Estimation of a Car Driver with
Depth Image Sensor by Using Particle Filter ................... 75
Norikazu Ikoma
X Contents
SNR Improvement of an Optical Wave Microphone Using a
Wavelet Network ............................................... 85
Takashi Samatsu, Yoshito Sonoda
Origin of Kanizsa Triangle Illusion.............................. 95
Tomoko Sakiyama, Aisato Sasaki, Yukio-Pegio Gunji
LTS-SVMR for Modeling of Nonlinear Systems with Noise
and Outliers .................................................... 105
Chen-Chia Chuang, Jin-Tsong Jeng, Guan-Yi Hu
Author Index................................................... 117