Abstract: In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.
Abstract: In this study, the locations and areas of commercial
accumulations were detected by using digital yellow page data. An
original buffering method that can accurately create polygons of
commercial accumulations is proposed in this paper.; by using this
method, distribution of commercial accumulations can be easily
created and monitored over a wide area. The locations, areas, and
time-series changes of commercial accumulations in the South Kanto
region can be monitored by integrating polygons of commercial
accumulations with the time-series data of digital yellow page data.
The circumstances of commercial accumulations were shown to vary
according to areas, that is, highly- urbanized regions such as the city
center of Tokyo and prefectural capitals, suburban areas near large
cities, and suburban and rural areas.
Abstract: In this paper we address the problem of musical style
classification, which has a number of applications like indexing in
musical databases or automatic composition systems. Starting from
MIDI files of real-world improvisations, we extract the melody track
and cut it into overlapping segments of equal length. From these
fragments, some numerical features are extracted as descriptors of
style samples. We show that a standard Bayesian classifier can be
conveniently employed to build an effective musical style classifier,
once this set of features has been extracted from musical data.
Preliminary experimental results show the effectiveness of the
developed classifier that represents the first component of a musical
audio retrieval system
Abstract: Textures are replications, symmetries and
combinations of various basic patterns, usually with some random
variation one of the gray-level statistics. This article proposes a
new approach to Segment texture images. The proposed approach
proceeds in 2 stages. First, in this method, local texture information
of a pixel is obtained by fuzzy texture unit and global texture
information of an image is obtained by fuzzy texture spectrum.
The purpose of this paper is to demonstrate the usefulness of fuzzy
texture spectrum for texture Segmentation.
The 2nd Stage of the method is devoted to a decision process,
applying a global analysis followed by a fine segmentation,
which is only focused on ambiguous points. The above Proposed
approach was applied to brain image to identify the components
of brain in turn, used to locate the brain tumor and its Growth
rate.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: Land degradation is of concern in many countries. People more and more must address the problems associated with the degradation of soil properties due to man. Increasingly, organic soil amendments, such as compost are being examined for their potential use in soil restoration and for preventing soil erosion. In the Czech Republic, compost is the most used to improve soil structure and increase the content of soil organic matter. Land reclamation / restoration is one of the ways to evaluate industrially produced compost because Czech farmers are not willing to use compost as organic fertilizer. The most common use of reclamation substrates in the Czech Republic is for the rehabilitation of landfills and contaminated sites.
This paper deals with the influence of reclamation substrates (RS) with different proportions of compost and sand on selected soil properties–chemical characteristics, nitrogen bioavailability, leaching of mineral nitrogen, respiration activity and plant biomass production. Chemical properties vary proportionally with addition of compost and sand to the control variant (topsoil). The highest differences between the variants were recorded in leaching of mineral nitrogen (varies from 1.36mg dm-3 in C to 9.09mg dm-3). Addition of compost to soil improves conditions for plant growth in comparison with soil alone. However, too high addition of compost may have adverse effects on plant growth. In addition, high proportion of compost increases leaching of mineral N. Therefore, mixture of 70% of soil with 10% of compost and 20% of sand may be recommended as optimal composition of RS.
Abstract: Recently, information security has become a key issue
in information technology as the number of computer security
breaches are exposed to an increasing number of security threats. A
variety of intrusion detection systems (IDS) have been employed for
protecting computers and networks from malicious network-based or
host-based attacks by using traditional statistical methods to new data
mining approaches in last decades. However, today's commercially
available intrusion detection systems are signature-based that are not
capable of detecting unknown attacks. In this paper, we present a
new learning algorithm for anomaly based network intrusion
detection system using decision tree algorithm that distinguishes
attacks from normal behaviors and identifies different types of
intrusions. Experimental results on the KDD99 benchmark network
intrusion detection dataset demonstrate that the proposed learning
algorithm achieved 98% detection rate (DR) in comparison with
other existing methods.
Abstract: This study aims to identify the current situation and
problems of environmental statement for major four home appliances
(refrigerators, washing machines, air conditioners and television
receivers) sold at online stores in Japan, and then to suggest how to
improve the situation, through a questionnaire survey conducted
among businesses that operate online stores and online malls with
multiple online stores. Results of the study boil down to:
(1) It is found out that environmental statement for the home
appliances at online stores have four problems; (i) less information
on “three Rs" and “chemical substances" than the one on “energy
conservation", (ii) cost for providing environmental statement, (iii)
issues associated with a label and mark placement, and (iv) issues
associated with energy conservation statement.
(2) Improvements are suggested for each of the four problems listed
above, and shown are (i) the effectiveness of, and need to promote, a
label and mark placement, (ii) cost burden on buyers, and (iii) need
of active efforts made by businesses and of dissemination of legal
regulations to businesses.
Abstract: This paper presents an algebraic approach to optimize
queries in domain-specific database management system
for protein structure data. The approach involves the introduction of
several protein structure specific algebraic operators to query the
complex data stored in an object-oriented database system. The
Protein Algebra provides an extensible set of high-level Genomic
Data Types and Protein Data Types along with a comprehensive
collection of appropriate genomic and protein functions. The paper
also presents a query translator that converts high-level query
specifications in algebra into low-level query specifications in
Protein-QL, a query language designed to query protein structure
data. The query transformation process uses a Protein Ontology that
serves the purpose of a dictionary.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: Heat pipes are used to control the thermal problem for
electronic cooling. It is especially difficult to dissipate heat to a heat
sink in an environment in space compared to earth. For solving this
problem, in this study, the Poiseuille (Po) number, which is the main
measure of the performance of a heat pipe, is studied by CFD; then, the
heat pipe performance is verified with experimental results. A heat
pipe is then fabricated for a spatial environment, and an in-house code
is developed. Further, a heat pipe subsystem, which consists of a heat
pipe, MLI (Multi Layer Insulator), SSM (Second Surface Mirror), and
radiator, is tested and correlated with the TMM (Thermal
Mathematical Model) through a commercial code. The correlation
results satisfy the 3K requirement, and the generated thermal model is
verified for application to a spatial environment.
Abstract: The main aim of this work is to establish the
capabilities of new green buildings to ascertain off-grid electricity
generation based on the integration of wind turbines in the
conceptual model of a rotating tower [2] in Dubai. An in depth
performance analysis of the WinWind 3.0MW [3] wind turbine is
performed. Data based on the Dubai Meteorological Services is
collected and analyzed in conjunction with the performance analysis
of this wind turbine. The mathematical model is compared with
Computational Fluid Dynamics (CFD) results based on a conceptual
rotating tower design model. The comparison results are further
validated and verified for accuracy by conducting experiments on a
scaled prototype of the tower design. The study concluded that
integrating wind turbines inside a rotating tower can generate enough
electricity to meet the required power consumption of the building,
which equates to a wind farm containing 9 horizontal axis wind
turbines located at an approximate area of 3,237,485 m2 [14].
Abstract: This paper study the segmented split capacitor
Digital-to-Analog Converter (DAC) implemented in a differentialtype
12-bit Successive Approximation Analog-to-Digital Converter
(SA-ADC). The series capacitance split array method employed as it
reduced the total area of the capacitors required for high resolution
DACs. A 12-bit regular binary array structure requires 2049 unit
capacitors (Cs) while the split array needs 127 unit Cs. These results
in the reduction of the total capacitance and power consumption of
the series split array architectures as to regular binary-weighted
structures. The paper will show the 12-bit DAC series split capacitor
with 4-bit thermometer coded DAC architectures as well as the
simulation and measured results.
Abstract: A combination of image fusion and quad tree decomposition method is used for detecting the sunspot trajectories in each month and computation of the latitudes of these trajectories in each solar hemisphere. Daily solar images taken with SOHO satellite are fused for each month and the result of fused image is decomposed with Quad Tree decomposition method in order to classifying the sunspot trajectories and then to achieve the precise information about latitudes of sunspot trajectories. Also with fusion we deduce some physical remarkable conclusions about sun magnetic fields behavior. Using quad tree decomposition we give information about the region on sun surface and the space angle that tremendous flares and hot plasma gases permeate interplanetary space and attack to satellites and human technical systems. Here sunspot images in June, July and August 2001 are used for studying and give a method to compute the latitude of sunspot trajectories in each month with sunspot images.
Abstract: Bendability is constrained by maximum top roller
load imparting capacity of the machine. Maximum load is
encountered during the edge pre-bending stage of roller bending.
Capacity of 3-roller plate bending machine is specified by
maximum thickness and minimum shell diameter combinations that
can be pre-bend for given plate material of maximum width.
Commercially available plate width or width of the plate that can be
accommodated on machine decides the maximum rolling width.
Original equipment manufacturers (OEM) provide the machine
capacity chart based on reference material considering perfectly
plastic material model. Reported work shows the bendability analysis
of heavy duty 3-roller plate bending machine. The input variables for
the industry are plate thickness, shell diameter and material property
parameters, as it is fixed by the design. Analytical models of
equivalent thickness, equivalent width and maximum width based on
power law material model were derived to study the bendability.
Equation of maximum width provides bendability for designed
configuration i.e. material property, shell diameter and thickness
combinations within the machine limitations. Equivalent thicknesses
based on perfectly plastic and power law material model were
compared for four different materials grades of C-Mn steel in order
to predict the bend-ability. Effect of top roller offset on the
bendability at maximum top roller load imparting capacity is
reported.
Abstract: Many agricultural and especially greenhouse
applications like plant inspection, data gathering, spraying and
selective harvesting could be performed by robots. In this paper
multiple nonholonomic robots are used in order to create a desired
formation scheme for screening solar energy in a greenhouse through
data gathering. The formation consists from a leader and a team
member equipped with appropriate sensors. Each robot is dedicated
to its mission in the greenhouse that is predefined by the
requirements of the application. The feasibility of the proposed
application includes experimental results with three unmanned
ground vehicles (UGV).
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.
Abstract: Problems on algebraical polynomials appear in many fields of mathematics and computer science. Especially the task of determining the roots of polynomials has been frequently investigated.Nonetheless, the task of locating the zeros of complex polynomials is still challenging. In this paper we deal with the location of zeros of univariate complex polynomials. We prove some novel upper bounds for the moduli of the zeros of complex polynomials. That means, we provide disks in the complex plane where all zeros of a complex polynomial are situated. Such bounds are extremely useful for obtaining a priori assertations regarding the location of zeros of polynomials. Based on the proven bounds and a test set of polynomials, we present an experimental study to examine which bound is optimal.
Abstract: The aim of this study was to screen for
microorganism that able to utilize 3-N-trimethylamino-1-propanol
(homocholine) as a sole source of carbon and nitrogen. The aerobic
degradation of homocholine has been found by a gram-positive
Rhodococcus sp. bacterium isolated from soil. The isolate was
identified as Rhodococcus sp. strain A4 based on the phenotypic
features, physiologic and biochemical characteristics, and
phylogenetic analysis. The cells of the isolated strain grown on both
basal-TMAP and nutrient agar medium displayed elementary
branching mycelia fragmented into irregular rod and coccoid
elements. Comparative 16S rDNA sequencing studies indicated that
the strain A4 falls into the Rhodococcus erythropolis subclade and
forms a monophyletic group with the type-strains of R. opacus, and
R. wratislaviensis. Metabolites analysis by capillary electrophoresis,
fast atom bombardment-mass spectrometry, and gas
chromatography- mass spectrometry, showed trimethylamine (TMA)
as the major metabolite beside β-alanine betaine and
trimethylaminopropionaldehyde. Therefore, the possible degradation
pathway of trimethylamino propanol in the isolated strain is through
consequence oxidation of alcohol group (-OH) to aldehyde (-CHO)
and acid (-COOH), and thereafter the cleavage of β-alanine betaine
C-N bonds yielded trimethylamine and alkyl chain.