Abstract: An important official knowledge in each country is to
have a comprehensive knowledge about markets of each group of
products. Drink markets are one the most important markets of each
country as a sub-group of nourishment markets. This paper is going
to study these markets in Iran. To do so, first, two drink products are
selected as pilot, including milk and concentrate. Then, for each
product, two groups of information are estimated for the last five
years, including 1) total consumption (demand) and 2) total
production. Finally, the two groups of productions are compared
statistically by means of two statistical tests called t test and Mann-
Whitney test. The implemented Different related tables and figures
are also illustrated to show the method more explicitly.
Abstract: The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. The concept of multivalued knowledgebase will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these extensions the concept of multivalued knowledge-base will be defined. This knowledge-base can be a possible background of a future agent-model.
Abstract: This paper proposes a model of adding relations between
members of the same level in a pyramid organization structure
which is a complete K-ary tree such that the communication of
information between every member in the organization becomes the
most efficient. When edges between one node and every other node
with the same depth N in a complete K-ary tree of height H are
added, an optimal depth N* = H is obtained by minimizing the total
path length which is the sum of lengths of shortest paths between
every pair of all nodes.
Abstract: This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
Abstract: The increase popularity of multimedia application especially in image processing places a great demand on efficient data storage and transmission techniques. Network communication such as wireless network can easily be intercepted and cause of confidential information leaked. Unfortunately, conventional compression and encryption methods are too slow; it is impossible to carry out real time secure image processing. In this research, Embedded Zerotree Wavelet (EZW) encoder which specially designs for wavelet compression is examined. With this algorithm, three methods are proposed to reduce the processing time, space and security protection that will be secured enough to protect the data.
Abstract: Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).
Abstract: The medical data statistical analysis often requires the
using of some special techniques, because of the particularities of
these data. The principal components analysis and the data clustering
are two statistical methods for data mining very useful in the medical
field, the first one as a method to decrease the number of studied
parameters, and the second one as a method to analyze the
connections between diagnosis and the data about the patient-s
condition. In this paper we investigate the implications obtained from
a specific data analysis technique: the data clustering preceded by a
selection of the most relevant parameters, made using the principal
components analysis. Our assumption was that, using the principal
components analysis before data clustering - in order to select and to
classify only the most relevant parameters – the accuracy of
clustering is improved, but the practical results showed the opposite
fact: the clustering accuracy decreases, with a percentage
approximately equal with the percentage of information loss reported
by the principal components analysis.
Abstract: Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect
data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.
Abstract: A multi-agent type robot for disaster response in calamity scene is proposed in this paper. The proposed grouped rescue robots can perform cooperative reconnaissance and surveillance to achieve a given rescue mission. The multi-agent rescue of dual set robot consists of one master set and three slave units. The research for this rescue robot system is going to detect at harmful environment where human is unreachable, such as the building is infected with virus or the factory has hazardous liquid in effluent. As a dual set robot, with Bluetooth and communication network, the master set can connect with slave units and send information back to computer by wireless and monitor. Therefore, rescuer can be informed the real-time information in a calamity area. Furthermore, each slave robot is able to obstacle avoidance by ultrasonic sensors, and encodes distance and location by compass. The master robot can integrate every devices information to increase the efficiency of prospected and research unknown area.
Abstract: Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.
Abstract: The purpose of this paper is to propose a text mining
approach to evaluate companies- practices on affective management.
Affective management argues that it is critical to take stakeholders-
affects into consideration during decision-making process, along with
the traditional numerical and rational indices. CSR reports published
by companies were collected as source information. Indices were
proposed based on the frequency and collocation of words relevant to
affective management concept using text mining approach to analyze
the text information of CSR reports. In addition, the relationships
between the results obtained using proposed indices and traditional
indicators of business performance were investigated using
correlation analysis. Those correlations were also compared between
manufacturing and non-manufacturing companies. The results of this
study revealed the possibility to evaluate affective management
practices of companies based on publicly available text documents.
Abstract: Air pollution is still considered as one of the major
environmental and health issues. There is enough research evidence
to show a strong relationship between exposure to air contaminants
and respiratory illnesses among children and adults. In this paper we
used the Copula approach to study a potential relationship between
selected air pollutants (PM10 and NO2) and hospital admissions for
respiratory diseases. Kendall-s tau and Spearman-s rho rank
correlation coefficients are calculated and used in Copula method.
This paper demonstrates that copulas can be used to provide
additional information as a measure of an association when compared
to the standard correlation coefficients. The results find a significant
correlation between the selected air pollutants and hospital
admissions for most of the selected respiratory illnesses.
Abstract: Abai Kunanbayev (1845-1904) was a great Kazakh
poet, composer and philosopher. Abai's main contribution to Kazakh
culture and folklore lies in his poetry, which expresses great
nationalism and grew out of Kazakh folk culture. Before him, most
Kazakh poetry was oral, echoing the nomadic habits of the people of
the Kazakh steppes. We want to introduce to abroad our country, its
history, tradition and culture. We can introduce it only through
translations. Only by reading the Kazakh works can foreign people
know who are kazakhs, the style of their life, their thoughts and so
on. All information comes only through translation. The main
requirement to a good translation is that it should be natural or that it
should read as smoothly as the original. Literary translation should
be adequate, should follow the original to the fullest. Translators
have to be loyal to original text, they shouldn-t give the way to
liberty.
Abstract: The management of the health-care wastes is one of
the most important problems in Istanbul, a city with more than 12
million inhabitants, as it is in most of the developing countries.
Negligence in appropriate treatment and final disposal of the healthcare
wastes can lead to adverse impacts to public health and to the
environment. This paper employs a fuzzy multi-criteria group
decision making approach, which is based on the principles of fusion
of fuzzy information, 2-tuple linguistic representation model, and
technique for order preference by similarity to ideal solution
(TOPSIS), to evaluate health-care waste (HCW) treatment
alternatives for Istanbul. The evaluation criteria are determined
employing nominal group technique (NGT), which is a method of
systematically developing a consensus of group opinion. The
employed method is apt to manage information assessed using multigranularity
linguistic information in a decision making problem with
multiple information sources. The decision making framework
employs ordered weighted averaging (OWA) operator that
encompasses several operators as the aggregation operator since it
can implement different aggregation rules by changing the order
weights. The aggregation process is based on the unification of
information by means of fuzzy sets on a basic linguistic term set
(BLTS). Then, the unified information is transformed into linguistic
2-tuples in a way to rectify the problem of loss information of other
fuzzy linguistic approaches.
Abstract: Advances in processors architecture, such as multicore,
increase the size of complexity of parallel computer systems.
With multi-core architecture there are different parallel languages
that can be used to run parallel programs. One of these languages is
OpenMP which embedded in C/Cµ or FORTRAN. Because of this
new architecture and the complexity, it is very important to evaluate
the performance of OpenMP constructs, kernels, and application
program on multi-core systems. Performance is the activity of
collecting the information about the execution characteristics of a
program. Performance tools consists of at least three interfacing
software layers, including instrumentation, measurement, and
analysis. The instrumentation layer defines the measured
performance events. The measurement layer determines what
performance event is actually captured and how it is measured by the
tool. The analysis layer processes the performance data and
summarizes it into a form that can be displayed in performance tools.
In this paper, a number of OpenMP performance tools are surveyed,
explaining how each is used to collect, analyse, and display data
collection.
Abstract: Proton transfer and hydrogen bonding are two aspects
of the chemistry of hydrogen that respectively govern the behaviour
and structure of many molecules, both simple and complex. All the
theoretical enol and keto conformations of 1,3-diphenyl-1,3-
propandion known as dibenzoylmethane (DBM), have been
investigated by means of atoms in molecules (AIM) theory. It was
found that the most stable conformers are those stabilized by
hydrogen bridges.The aim of the present paper is a thorough
conformational analysis of DBM (with special attention on chelated
cis-enol conformers) in order to obtain detailed information on the
geometrical parameters, relative stabilities and rotational motion of
the phenyl groups. It is also important to estimate the barrier height
for ptoton transfer and hydrogen bond strength, which are the main
factors governing conformational stability.
Abstract: Soft set theory was initiated by Molodtsov in 1999. In the past years, this theory had been applied to many branches of mathematics, information science and computer science. In 2003, Maji et al. introduced some operations of soft sets and gave some operational rules. Recently, some of these operational rules are pointed out to be not true. Furthermore, Ali et al., in their paper, introduced and discussed some new operations of soft sets. In this paper, we further investigate these operational rules given by Maji et al. and Ali et al.. We obtain some sufficient-necessary conditions such that corresponding operational rules hold and give correct forms for some operational rules. These results will be help for us to use rightly operational rules of soft sets in research and application of soft set theory.
Abstract: The most important property of the Gene Ontology is
the terms. These control vocabularies are defined to provide
consistent descriptions of gene products that are shareable and
computationally accessible by humans, software agent, or other
machine-readable meta-data. Each term is associated with
information such as definition, synonyms, database references, amino
acid sequences, and relationships to other terms. This information has
made the Gene Ontology broadly applied in microarray and
proteomic analysis. However, the process of searching the terms is
still carried out using traditional approach which is based on keyword
matching. The weaknesses of this approach are: ignoring semantic
relationships between terms, and highly depending on a specialist to
find similar terms. Therefore, this study combines semantic similarity
measure and genetic algorithm to perform a better retrieval process
for searching semantically similar terms. The semantic similarity
measure is used to compute similitude strength between two terms.
Then, the genetic algorithm is employed to perform batch retrievals
and to handle the situation of the large search space of the Gene
Ontology graph. The computational results are presented to show the
effectiveness of the proposed algorithm.
Abstract: In the upgrade process of enterprise information
systems, how to deal with and utilize those legacy systems affects the
efficiency of construction and development of the new system. We
propose an evaluation system, which comprehensively describes the
capacity of legacy information systems in five aspects. Then we
propose a practical legacy systems evaluation method. Base on the
evaluation result, we can determine the current state of legacy system
which was evaluated.
Abstract: This paper explain about analysis and design a business directory for micro-scale businesses, small and medium enterprises (SMEs). Business Directory, if implemented will facilitate and optimize the access of SMEs to ease suppliers access to marketing. Business Directory will be equipped with the power of geocoding, so each location can be easily viewed SMEs on the map. The map will be constructed by using the functionality of a webbased Google Maps API. The information presented in the form of multimedia that can be more interesting and interactive. The method used to achieve the goal are: observation; interviews; modeling and classifying business directory for SMEs.