Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.
Abstract: Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
Abstract: Post-anthesis drought stress is the most important
problem affecting wheat production in dryland fields, specially in
Mediterranean regions. The main objective of this research was to
evaluate drought tolerance indices in dryland wheat genotypes under
post-anthesis drought stress. The research was including two different
experiments. In each experiment, twenty dryland bread wheat
genotypes were sown in a randomized complete blocks design
(RCBD) with three replications. One of experiments belonged to
rain-fed conditions (post-anthesis drought stress) and other
experiment was under non-stress conditions (with supplemental
irrigation). Different drought tolerance indices include Stress
Tolerance (Tol), Mean Productivity (MP), Geometric Mean
Productivity (GMP), Stress Susceptibility Index (SSI), Stress
Tolerance Index (STI), Harmonic Mean (HAM), Yield Index (YI)
and Yield Stability Index (YSI) were evaluate based on grain yield
under rain-fed (Ys) and supplemental irrigation (Yp) environments.
G10 and G12 were the most tolerant genotypes based on TOL and
SSI. But, based on MP, GMP, STI, HAM and YI indices, G1 and G2
were selected. STI, GMP and MP indices had high correlation with
grain yield under rain-fed and supplementary irrigation conditions
and were recognized as appropriate indices to identify genotypes with
high grain yield and low sensitivity to drought stress environments.
Abstract: This study proposes novel hybrid social network analysis and collaborative filtering approach to enhance the performance of recommender systems. The proposed model selects subgroups of users in Internet community through social network analysis (SNA), and then performs clustering analysis using the information about subgroups. Finally, it makes recommendations using cluster-indexing CF based on the clustering results. This study tries to use the cores in subgroups as an initial seed for a conventional clustering algorithm. This model chooses five cores which have the highest value of degree centrality from SNA, and then performs clustering analysis by using the cores as initial centroids (cluster centers). Then, the model amplifies the impact of friends in social network in the process of cluster-indexing CF.
Abstract: This paper has as its main aim to analyse how
corporate web pages can become an essential tool in order to detect
strategic trends by firms or sectors, and even a primary source for
benchmarking. This technique has made it possible to identify the key
issues in the strategic management of the most excellent large Spanish
firms and also to describe trends in their long-range planning, a way of
working that can be generalised to any country or firm group. More
precisely, two objectives were sought. The first one consisted in showing
the way in which corporate websites make it possible to obtain direct
information about the strategic variables which can define firms. This
tool is dynamic (since web pages are constantly updated) as well as
direct and reliable, since the information comes from the firm itself, not
from comments of third parties (such as journalists, academicians,
consultants...). When this information is analysed for a group of firms,
one can observe their characteristics in terms of both managerial tasks
and business management. As for the second objective, the methodology
proposed served to describe the corporate profile of the large Spanish
enterprises included in the Ibex35 (the Ibex35 or Iberia Index is the
reference index in the Spanish Stock Exchange and gathers periodically
the 35 most outstanding Spanish firms). An attempt is therefore made to
define the long-range planning that would be characteristic of the largest
Spanish firms.
Abstract: In this paper, we present a novel objective nonreference
performance assessment algorithm for image fusion. It takes
into account local measurements to estimate how well the important
information in the source images is represented by the fused image.
The metric is based on the Universal Image Quality Index and uses
the similarity between blocks of pixels in the input images and the
fused image as the weighting factors for the metrics. Experimental
results confirm that the values of the proposed metrics correlate well
with the subjective quality of the fused images, giving a significant
improvement over standard measures based on mean squared error
and mutual information.
Abstract: Silicon is a beneficial element for plant growth. It
helps plants to overcome multiple stresses, alleviates metal toxicity
and improves nutrient imbalance. Field experiment was conducted as
split-split plot arranged in a randomized complete block design with
four replications. Irrigation system include continues flooding and
deficit as main plots and nitrogen rates N0, N46, N92, and N138 kg/ha
as sub plots and silicon rates Si0 & Si500 kg/ha as sub-subplots.
Results indicate that grain yield had not significant difference
between irrigation systems. Flooding irrigation had higher biological
yield than deficit irrigation whereas, no significant difference in grain
and straw yield. Nitrogen application increased grain, biological and
straw yield. Silicon application increased grain, biological and straw
yield but, decreased harvest index. Flooding irrigation had higher
number of total tillers / hill than deficit irrigation, but deficit
irrigation had higher number of fertile tillers / hill than flooding
irrigation. Silicon increased number of filled spikelet and decreased
blank spikelet. With high nitrogen application decreased 1000-grain
weight. It can be concluded that if the nitrogen application was high
and water supplied was available we could have silicon application
until increase grain yield.
Abstract: The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,
April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.
Abstract: This paper describes the optimization of a complex
dairy farm simulation model using two quite different methods of
optimization, the Genetic algorithm (GA) and the Lipschitz
Branch-and-Bound (LBB) algorithm. These techniques have been
used to improve an agricultural system model developed by Dexcel
Limited, New Zealand, which describes a detailed representation of
pastoral dairying scenarios and contains an 8-dimensional parameter
space. The model incorporates the sub-models of pasture growth and
animal metabolism, which are themselves complex in many cases.
Each evaluation of the objective function, a composite 'Farm
Performance Index (FPI)', requires simulation of at least a one-year
period of farm operation with a daily time-step, and is therefore
computationally expensive. The problem of visualization of the
objective function (response surface) in high-dimensional spaces is
also considered in the context of the farm optimization problem.
Adaptations of the sammon mapping and parallel coordinates
visualization are described which help visualize some important
properties of the model-s output topography. From this study, it is
found that GA requires fewer function evaluations in optimization
than the LBB algorithm.
Abstract: This study adopted previous fault patterns, results of
detection analysis, historical records and data, and experts-
experiences to establish fuzzy principles and estimate the failure
probability index of components of a power transformer. Considering
that actual parameters and limiting conditions of parameters may
differ, this study used the standard data of IEC, IEEE, and CIGRE as
condition parameters. According to the characteristics of each
condition parameter, relative degradation was introduced to reflect the
degree of influence of the factors on the transformer condition. The
method of fuzzy mathematics was adopted to determine the
subordinate function of the transformer condition. The calculation
used the Matlab Fuzzy Tool Box to select the condition parameters of
coil winding, iron core, bushing, OLTC, insulating oil and other
auxiliary components and factors (e.g., load records, performance
history, and maintenance records) of the transformer to establish the
fuzzy principles. Examples were presented to support the rationality
and effectiveness of the evaluation method of power transformer
performance conditions, as based on fuzzy comprehensive evaluation.
Abstract: In order to investigate water deficit stress on 24 of
soybean (Glycine Max. L) cultivars and lines in temperate climate, an
experiment was conducted in Iran Seed and Plant Improvement
Institute. Stress levels were irrigation after evaporation of 50, 100,
150 mm water from pan, class A. Randomized Completely Block
Design was arranged for each stress levels. Some traits such as, node
number, plant height, pod number per area, grain number per pod,
grain number per area, 1000 grains weight, grain yield and harvest
index were measured. Results showed that water deficit stress had
significant effect on node number, plant height, pod number per area,
grain number per pod, grain number per area, 1000 grains weight and
harvest index. Also all of agronomic traits except harvest index
influenced significantly by cultivars and lines. The least and most
grain yield was belonged to Ronak X Williams and M41 x Clark
respectively.
Abstract: In this paper, an artificial intelligent technique for
robust digital image watermarking in multiwavelet domain is
proposed. The embedding technique is based on the quantization
index modulation technique and the watermark extraction process
does not require the original image. We have developed an
optimization technique using the genetic algorithms to search for
optimal quantization steps to improve the quality of watermarked
image and robustness of the watermark. In addition, we construct a
prediction model based on image moments and back propagation
neural network to correct an attacked image geometrically before the
watermark extraction process begins. The experimental results show
that the proposed watermarking algorithm yields watermarked image
with good imperceptibility and very robust watermark against various
image processing attacks.
Abstract: Larval survey was carried out in 6 localities in the
urban areas (Putrajaya) and suburban areas (Kuala Selangor) from
January until December 2010. A total of 520 representative
households in 6 localities were selected. Breeding habitats were
sampled outdoors in the surroundings of housing areas. The study
indicated that the most predominant species found in both areas was
Aedes albopictus with the gardening utensil as a preferred breeding
microhabitat for Putrajaya, in contrast to the artificial containers for
Kuala Selangor. From a total of 1083 mosquito larvae species, 984
were Aedes albopictus larvae, 67 positive larvae of Aedes aegypti
and 32 of Culex larvae. Aedes Index and Container Index were
elevated in Putrajaya with 13% and 11% respectively which is higher
than the standard given by the Ministry of Health, Malaysia. This
results implicating dengue-sensitive skewed to the urban areas.
Breteau Index result also above the standard in both study locations.
Abstract: The possibility of using cassava residue containing
49.66% starch, 21.47% cellulose, 12.97% hemicellulose, and 21.86%
lignin as a raw material to produce glucose using enzymatic
hydrolysis was investigated. In the experiment, each reactor
contained the cassava residue, bacteria cells, and production medium.
The effects of particles size (40 mesh and 60 mesh) and strains of
bacteria (A002 and M015) isolated from Thai higher termites,
Microcerotermes sp., on the glucose concentration at 37°C were
focused. High performance liquid chromatography (HPLC) with a
refractive index detector was used to determine the quantity of
glucose. The maximum glucose concentration obtained at 37°C using
strain A002 and 60 mesh of the cassava residue was 1.51 g/L at 10 h.
Abstract: EGOTHOR is a search engine that indexes the Web
and allows us to search the Web documents. Its hit list contains URL
and title of the hits, and also some snippet which tries to shortly
show a match. The snippet can be almost always assembled by an
algorithm that has a full knowledge of the original document (mostly
HTML page). It implies that the search engine is required to store
the full text of the documents as a part of the index.
Such a requirement leads us to pick up an appropriate compression
algorithm which would reduce the space demand. One of the solutions
could be to use common compression methods, for instance gzip or
bzip2, but it might be preferable if we develop a new method which
would take advantage of the document structure, or rather, the textual
character of the documents.
There already exist a special compression text algorithms and
methods for a compression of XML documents. The aim of this
paper is an integration of the two approaches to achieve an optimal
level of the compression ratio
Abstract: The data exchanged on the Web are of different nature
from those treated by the classical database management systems;
these data are called semi-structured data since they do not have a
regular and static structure like data found in a relational database;
their schema is dynamic and may contain missing data or types.
Therefore, the needs for developing further techniques and
algorithms to exploit and integrate such data, and extract relevant
information for the user have been raised. In this paper we present
the system OSIX (Osiris based System for Integration of XML
Sources). This system has a Data Warehouse model designed for the
integration of semi-structured data and more precisely for the
integration of XML documents. The architecture of OSIX relies on
the Osiris system, a DL-based model designed for the representation
and management of databases and knowledge bases. Osiris is a viewbased
data model whose indexing system supports semantic query
optimization. We show that the problem of query processing on a
XML source is optimized by the indexing approach proposed by
Osiris.
Abstract: With the rapid development in the field of life
sciences and the flooding of genomic information, the need for faster
and scalable searching methods has become urgent. One of the
approaches that were investigated is indexing. The indexing methods
have been categorized into three categories which are the lengthbased
index algorithms, transformation-based algorithms and mixed
techniques-based algorithms. In this research, we focused on the
transformation based methods. We embedded the N-gram method
into the transformation-based method to build an inverted index
table. We then applied the parallel methods to speed up the index
building time and to reduce the overall retrieval time when querying
the genomic database. Our experiments show that the use of N-Gram
transformation algorithm is an economical solution; it saves time and
space too. The result shows that the size of the index is smaller than
the size of the dataset when the size of N-Gram is 5 and 6. The
parallel N-Gram transformation algorithm-s results indicate that the
uses of parallel programming with large dataset are promising which
can be improved further.
Abstract: Interpretation of aerial images is an important task in
various applications. Image segmentation can be viewed as the essential
step for extracting information from aerial images. Among many
developed segmentation methods, the technique of clustering has been
extensively investigated and used. However, determining the number
of clusters in an image is inherently a difficult problem, especially
when a priori information on the aerial image is unavailable. This
study proposes a support vector machine approach for clustering
aerial images. Three cluster validity indices, distance-based index,
Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative
measures of the quality of clustering results. Comparisons on the
effectiveness of these indices and various parameters settings on the
proposed methods are conducted. Experimental results are provided
to illustrate the feasibility of the proposed approach.
Abstract: There are three approaches to complete Bayesian
Network (BN) model construction: total expert-centred, total datacentred,
and semi data-centred. These three approaches constitute the
basis of the empirical investigation undertaken and reported in this
paper. The objective is to determine, amongst these three
approaches, which is the optimal approach for the construction of a
BN-based model for the performance assessment of students-
laboratory work in a virtual electronic laboratory environment. BN
models were constructed using all three approaches, with respect to
the focus domain, and compared using a set of optimality criteria. In
addition, the impact of the size and source of the training, on the
performance of total data-centred and semi data-centred models was
investigated. The results of the investigation provide additional
insight for BN model constructors and contribute to literature
providing supportive evidence for the conceptual feasibility and
efficiency of structure and parameter learning from data. In addition,
the results highlight other interesting themes.
Abstract: The objective of this paper is to construct a creativity
composite index designed to capture the growing role of creativity in
driving economic and social development for the 27 European Union
countries.
The paper proposes a new approach for the measurement of EU-27
creative potential and for determining its capacity to attract and
develop creative human capital. We apply a modified version of the
3T model developed by Richard Florida and Irene Tinagli for
constructing a Euro-Creativity Index. The resulting indexes establish
a quantitative base for policy makers, supporting their efforts to
determine the contribution of creativity to economic development.