Abstract: This paper presents a solution for the behavioural
animation of autonomous virtual agent navigation in virtual environments.
We focus on using Dempster-Shafer-s Theory of Evidence
in developing visual sensor for virtual agent. The role of the visual
sensor is to capture the information about the virtual environment
or identifie which part of an obstacle can be seen from the position
of the virtual agent. This information is require for vitual agent to
coordinate navigation in virtual environment. The virual agent uses
fuzzy controller as a navigation system and Fuzzy α - level for
the action selection method. The result clearly demonstrates the path
produced is reasonably smooth even though there is some sharp turn
and also still not diverted too far from the potential shortest path.
This had indicated the benefit of our method, where more reliable
and accurate paths produced during navigation task.
Abstract: Feature selection plays an important role in applications with high dimensional data. The assessment of the stability of feature selection/ranking algorithms becomes an important issue when the dataset is small and the aim is to gain insight into the underlying process by analyzing the most relevant features. In this work, we propose a graphical approach that enables to analyze the similarity between feature ranking techniques as well as their individual stability. Moreover, it works with whatever stability metric (Canberra distance, Spearman's rank correlation coefficient, Kuncheva's stability index,...). We illustrate this visualization technique evaluating the stability of several feature selection techniques on a spectral binary dataset. Experimental results with a neural-based classifier show that stability and ranking quality may not be linked together and both issues have to be studied jointly in order to offer answers to the domain experts.
Abstract: In this paper a simple terrain evaluation method for
hexapod robot is introduced. This method is based on feet coordinate
evaluation when all are on the ground. Depending on the feet
coordinate differences the local terrain evaluation is possible. Terrain
evaluation is necessary for right gait selection and/or body position
correction. For terrain roughness evaluation three planes are plotted:
two of them as definition points use opposite feet coordinates, third
coincides with the robot body plane. The leaning angle of body plane
is evaluated measuring gravity force using three-axis accelerometer.
Terrain roughness evaluation method is based on angle estimation
between normal vectors of these planes. Aim of this work is to
present a simple method for embedded robot controller, allowing to
find the best further movement settings.
Abstract: With increasing number of wireless devices like
laptops, Wi-Fi Web Cams, network extenders, etc., a new kind of
problems appeared, mostly related to poor Wi-Fi throughput or
communication problems. In this paper an investigation on wireless
networks and it-s saturation in Vilnius City and its surrounding is
presented, covering the main problems of wireless saturation and
network load during day. Also an investigation on wireless channel
selection and noise levels were made, showing the impact of
neighbor AP to signal and noise levels and how it changes during the
day.
Abstract: The objective of this study is to propose a statistical
modeling method which enables simultaneous term structure
estimation of the risk-free interest rate, hazard and loss given default,
incorporating the characteristics of the bond issuing company such as
credit rating and financial information. A reduced form model is used
for this purpose. Statistical techniques such as spline estimation and
Bayesian information criterion are employed for parameter estimation
and model selection. An empirical analysis is conducted using the
information on the Japanese bond market data. Results of the
empirical analysis confirm the usefulness of the proposed method.
Abstract: In this paper the application of rule mining in order to
review the effective factors on supplier selection is reviewed in the
following three sections 1) criteria selecting and information
gathering 2) performing association rule mining 3) validation and
constituting rule base. Afterwards a few of applications of rule base
is explained. Then, a numerical example is presented and analyzed
by Clementine software. Some of extracted rules as well as the
results are presented at the end.
Abstract: Directive 2009/28/CE establishes, as obligatory objective, a share of renewable energies on energetic consumption of 20%, in European Union, in 2020 However, such European normative gives freedom to member states in the selection of the renewable promotion mechanism that allows them to obtain that objective. In this paper, we analyze the main characteristics of the promotion mechanisms of renewable energy used in the countries that shape the Electricity Iberian Market (Spain and Portugal) and the results in employment. The importance of these countries is given by the great increasing of the renewable energies which suppose a share higher than 30% of the overall generation in 2010. Therefore, this research paper can serve as the basis for the learning of other countries with regard to the main advantages that entail the use of a feed-in tariff system.
Abstract: Recently ORC(Organic Rankine Cycle) has attracted
much attention due to its potential in reducing consumption of fossil
fuels and its favorable characteristics to exploit low-grade heat sources.
In this work thermodynamic performance of ORC with superheating of
vapor is comparatively assessed for various working fluids. Special
attention is paid to the effects of system parameters such as the evaporating
temperature and the turbine inlet temperature on the characteristics
of the system such as maximum possible work extraction from
the given source, volumetric flow rate per 1 kW of net work and
quality of the working fluid at turbine exit as well as thermal and
exergy efficiencies. Results show that for a given source the thermal
efficiency increases with decrease of the superheating but exergy
efficiency may have a maximum value with respect to the superheating
of the working fluid. Results also show that in selection of working
fluid it is required to consider various criteria of performance characteristics
as well as thermal efficiency.
Abstract: We have proposed an information filtering system
using index word selection from a document set based on the
topics included in a set of documents. This method narrows
down the particularly characteristic words in a document set
and the topics are obtained by Sparse Non-negative Matrix
Factorization. In information filtering, a document is often
represented with the vector in which the elements correspond
to the weight of the index words, and the dimension of the
vector becomes larger as the number of documents is
increased. Therefore, it is possible that useless words as index
words for the information filtering are included. In order to
address the problem, the dimension needs to be reduced. Our
proposal reduces the dimension by selecting index words
based on the topics included in a document set. We have
applied the Sparse Non-negative Matrix Factorization to the
document set to obtain these topics. The filtering is carried out
based on a centroid of the learning document set. The centroid
is regarded as the user-s interest. In addition, the centroid is
represented with a document vector whose elements consist of
the weight of the selected index words. Using the English test
collection MEDLINE, thus, we confirm the effectiveness of
our proposal. Hence, our proposed selection can confirm the
improvement of the recommendation accuracy from the other
previous methods when selecting the appropriate number of
index words. In addition, we discussed the selected index
words by our proposal and we found our proposal was able to
select the index words covered some minor topics included in
the document set.
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: The low power wireless sensor devices which usually
uses the low power wireless private area network (IEEE 802.15.4)
standard are being widely deployed for various purposes and in
different scenarios. IPv6 low power wireless private area network
(6LoWPAN) was adopted as part of the IETF standard for the
wireless sensor devices so that it will become an open standard
compares to other dominated proprietary standards available in the
market. 6LoWPAN also allows the integration and communication of
sensor nodes with the Internet more viable. This paper presents a
comparative study on different available IPv6 platforms for wireless
sensor networks including open and close sources. It also discusses
about the platforms used by these stacks. Finally it evaluates and
provides appropriate suggestions which can be use for selection of
required IPv6 stack for low power devices.
Abstract: A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.
Abstract: In a representative democracy political parties
promote vital competition on different policy issues and play
essential roles by offering ideological alternatives. They also give
channels for citizens- participation in government decision-making
processes and they are significant conduits and interpreters of
information about government. This paper attempts to examine how
opposition political parties and rebel fronts emerged in Ethiopia, and
examines their present conditions. In this paper, selected case studies
of political parties and rebel fronts are included to highlight the status
and the role of opposition groups in the country in the three
successive administrations: Haile Selassie (1930-1974), Derg (1974-
1991), and EPRDF (1991-Present).
Abstract: The decision of information technology (IT) outsourcing requires close attention to the evaluation of supplier selection process because the selection decision involves conflicting multiple criteria and is replete with complex decision making problems. Selecting the most appropriate suppliers is considered an important strategic decision that may impact the performance of outsourcing engagements. The objective of this paper is to aid decision makers to evaluate and assess possible IT outsourcing suppliers. An axiomatic design based fuzzy group decision making is adopted to evaluate supplier alternatives. Finally, a case study is given to demonstrate the potential of the methodology. KeywordsIT outsourcing, Supplier selection, Multi-criteria decision making, Axiomatic design, Fuzzy logic.
Abstract: Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.
Abstract: In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.
Abstract: The objective of this paper is to investigate a new
approach based on the idea of pictograms for food portion size. This
approach adopts the model of the United States Pharmacopeia- Drug
Information (USP-DI). The representation of each food portion size
composed of three parts: frame, the connotation of dietary portion
sizes and layout. To investigate users- comprehension based on this
approach, two experiments were conducted, included 122 Taiwanese
people, 60 male and 62 female with ages between 16 and 64 (divided
into age groups of 16-30, 31-45 and 46-64). In Experiment 1, the mean
correcting rate of the understanding level of food items is 48.54%
(S.D.= 95.08) and the mean response time 2.89sec (S.D.=2.14). The
difference on the correct rates for different age groups is significant
(P*=0.00
Abstract: This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.
Abstract: One of the most important parameters to develop and
manage urban areas is appropriate selection of land surface to
develop green spaces in these areas. In this study, in order to identify
the most appropriate sites and areas cultivated for ornamental species
in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images
due to extract the most important effective climatic and adaphic
parameters for growth ornamental species were used. After geometric
and atmospheric corrections applied, to enhance accuracy of multi
spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D
panchromatic band (PAN) was performed. After field sampling to
evaluate the correlation between different factors in surface soil
sampling location and different bands digital number (DN) of ETM+
sensor on the same points, correlation tables formed using the best
computational model and the map of physical and chemical
parameters of soil was produced. Then the accuracy of them was
investigated by using kappa coefficient. Finally, according to
produced maps, the best areas for cultivation of recommended
species were introduced.
Abstract: This paper proposes a low-voltage and low-power
fully integrated digitally tuned continuous-time channel selection
filter for WiMAX applications. A 5th-order elliptic low-pass filter is
realized in a Gm-C topology. The bandwidth of the fully differential
filter is reconfigurable from 2.5MHz to 20MHz (8x) for different
requirements in WiMAX applications. The filter is simulated in a
standard 90nm CMOS process. Simulation results show the THD
(@Vout =100mVpp) is less than -66dB. The in-band ripple of the
filter is about 0.15dB. The filter consumes 1.5mW from a supply
voltage of 0.9V.