Abstract: The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.
Abstract: Nowadays, without the awareness of consumer
behavior and correct understanding of it, it is not possible for organizations to take appropriate measures to meet the consumer
needs and demands. The aim of this paper is the identification and
prioritization of the factors affecting the consumer behavior based on
the product value. The population of the study includes all the
consumers of furniture producing firms in East Azarbaijan province,
Iran. The research sample includes 93 people selected by the sampling formula in unlimited population. The data collection
instrument was a questionnaire, the validity of which was confirmed
through face validity and the reliability of which was determined,
using Cronbach's alpha coefficient. The Kolmogorov-Smironov test
was used to test data normality, the t-test for identification of factors
affecting the product value, and Friedman test for prioritizing the
factors. The results show that quality, satisfaction, styling, price, finishing operation, performance, safety, worth, shape, use, and
excellence are placed from 1 to 11 priorities, respectively.
Abstract: In this work, the primary compressive strength
components of human femur trabecular bone are qualitatively
assessed using image processing and wavelet analysis. The Primary
Compressive (PC) component in planar radiographic femur trabecular
images (N=50) is delineated by semi-automatic image processing
procedure. Auto threshold binarization algorithm is employed to
recognize the presence of mineralization in the digitized images. The
qualitative parameters such as apparent mineralization and total area
associated with the PC region are derived for normal and abnormal
images.The two-dimensional discrete wavelet transforms are utilized
to obtain appropriate features that quantify texture changes in medical
images .The normal and abnormal samples of the human femur are
comprehensively analyzed using Harr wavelet.The six statistical
parameters such as mean, median, mode, standard deviation, mean
absolute deviation and median absolute deviation are derived at level
4 decomposition for both approximation and horizontal wavelet
coefficients. The correlation coefficient of various wavelet derived
parameters with normal and abnormal for both approximated and
horizontal coefficients are estimated. It is seen that in almost all cases
the abnormal show higher degree of correlation than normals. Further
the parameters derived from approximation coefficient show more
correlation than those derived from the horizontal coefficients. The
parameters mean and median computed at the output of level 4 Harr
wavelet channel was found to be a useful predictor to delineate the
normal and the abnormal groups.
Abstract: Starting from a biologically inspired framework, Gabor filters were built up from retinal filters via LMSE algorithms. Asubset of retinal filter kernels was chosen to form a particular Gabor filter by using a weighted sum. One-dimensional optimization approaches were shown to be inappropriate for the problem. All model parameters were fixed with biological or image processing constraints. Detailed analysis of the optimization procedure led to the introduction of a minimization constraint. Finally, quantization of weighting factors was investigated. This resulted in an optimized cascaded structure of a Gabor filter bank implementation with lower computational cost.
Abstract: Data clustering is an important data exploration technique
with many applications in data mining. We present an enhanced
version of the well known single link clustering algorithm. We will
refer to this algorithm as DCBOR. The proposed algorithm alleviates
the chain effect by removing the outliers from the given dataset.
So this algorithm provides outlier detection and data clustering
simultaneously. This algorithm does not need to update the distance
matrix, since the algorithm depends on merging the most k-nearest
objects in one step and the cluster continues grow as long as possible
under specified condition. So the algorithm consists of two phases;
at the first phase, it removes the outliers from the input dataset. At
the second phase, it performs the clustering process. This algorithm
discovers clusters of different shapes, sizes, densities and requires
only one input parameter; this parameter represents a threshold for
outlier points. The value of the input parameter is ranging from 0 to
1. The algorithm supports the user in determining an appropriate
value for it. We have tested this algorithm on different datasets
contain outlier and connecting clusters by chain of density points,
and the algorithm discovers the correct clusters. The results of
our experiments demonstrate the effectiveness and the efficiency of
DCBOR.
Abstract: Today with the rapid growth of telecommunications equipment, electronic and developing more and more networks of power, influence of electromagnetic waves on one another has become hot topic discussions. So in this article, this issue and appropriate mechanisms for EMC operations have been presented. First, a source of alternating current (50 Hz) and a clear victim in a certain distance from the source is placed. With this simple model, the effects of electromagnetic radiation from the source to the victim will be investigated and several methods to reduce these effects have been presented. Therefore passive and active shields have been used. In some steps, shielding effectiveness of proposed shields will be compared. . It should be noted that simulations have been done by the finite element method (FEM).
Abstract: Automated discovery of hierarchical structures in
large data sets has been an active research area in the recent past.
This paper focuses on the issue of mining generalized rules with crisp
hierarchical structure using Genetic Programming (GP) approach to
knowledge discovery. The post-processing scheme presented in this
work uses flat rules as initial individuals of GP and discovers
hierarchical structure. Suitable genetic operators are proposed for the
suggested encoding. Based on the Subsumption Matrix(SM), an
appropriate fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the discovered
hierarchy. Experimental results are presented to demonstrate the
performance of the proposed algorithm.
Abstract: Digital news with a variety topics is abundant on the
internet. The problem is to classify news based on its appropriate
category to facilitate user to find relevant news rapidly. Classifier
engine is used to split any news automatically into the respective
category. This research employs Support Vector Machine (SVM) to
classify Indonesian news. SVM is a robust method to classify
binary classes. The core processing of SVM is in the formation of an
optimum separating plane to separate the different classes. For
multiclass problem, a mechanism called one against one is used to
combine the binary classification result. Documents were taken
from the Indonesian digital news site, www.kompas.com. The
experiment showed a promising result with the accuracy rate of 85%.
This system is feasible to be implemented on Indonesian news
classification.
Abstract: Avalanche release of snow has been modeled in the present studies. Snow is assumed to be represented by semi-solid and the governing equations have been studied from the concept of continuum approach. The dynamical equations have been solved for two different zones [starting zone and track zone] by using appropriate initial and boundary conditions. Effect of density (ρ), Eddy viscosity (η), Slope angle (θ), Slab depth (R) on the flow parameters have been observed in the present studies. Numerical methods have been employed for computing the non linear differential equations. One of the most interesting and fundamental innovation in the present studies is getting initial condition for the computation of velocity by numerical approach. This information of the velocity has obtained through the concept of fracture mechanics applicable to snow. The results on the flow parameters have found to be in qualitative agreement with the published results.
Abstract: In this article, by means of examination of Bolshevists
Turkistanskie Vedomosti" newspaper and “Erikti Oylar Organi" and
“Turkistanskyi Vestnik" newspapers which had been published
during 1917-1918, the fact that “Turkistan Governorship" established
in city of Kokand in November of 1917, within the framework of
former tsarist Russia Turkistan general-governorship, was the legal
government formed as a requisition of people of Turkistan was
proved. An examination of these two newspapers providing
information regarding history of “Turkistan Autonomy" but having
opposite to each other views makes it possible to obtain valuable data
concerning history of autonomy which was inappropriately
misrepresented during Soviet period.
Abstract: Background: Blunt aortic trauma (BAT) includes
various morphological changes that occur during deceleration,
acceleration and/or body compression in traffic accidents. The
various forms of BAT, from limited laceration of the intima to
complete transection of the aorta, depends on the force acting on the
vessel wall and the tolerance of the aorta to injury. The force depends
on the change in velocity, the dynamics of the accident and of the
seating position in the car. Tolerance to aortic injury depends on the
anatomy, histological structure and pathomorphological alterations
due to aging or disease of the aortic wall.
An overview of the literature and medical documentation reveals
that different terms are used to describe certain forms of BAT, which
can lead to misinterpretation of findings or diagnoses. We therefore,
propose a classification that would enable uniform systematic
screening of all forms of BAT. We have classified BAT into three
morphologycal types: TYPE I (intramural), TYPE II (transmural) and
TYPE III (multiple) aortic ruptures with appropriate subtypes.
Methods: All car accident casualties examined at the Institute of
Forensic Medicine from 2001 to 2009 were included in this
retrospective study. Autopsy reports were used to determine the
occurrence of each morphological type of BAT in deceased drivers,
front seat passengers and other passengers in cars and to define the
morphology of BAT in relation to the accident dynamics and the age
of the fatalities.
Results: A total of 391 fatalities in car accidents were included in
the study. TYPE I, TYPE II and TYPE III BAT were observed in
10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in
drivers, front seat and other passengers was 36,7%, 43,1% and
28,6%, respectively. In frontal collisions, the incidence of BAT was
32,7%, in lateral collisions 54,2%, and in other traffic accidents
29,3%. The average age of fatalities with BAT was 42,8 years and of
those without BAT 39,1 years.
Conclusion: Identification and early recognition of the risk factors
of BAT following a traffic accident is crucial for successful treatment
of patients with BAT. Front seat passengers over 50 years of age who
have been injured in a lateral collision are the most at risk of BAT.
Abstract: This paper presented a novel combined cycle of air separation and natural gas liquefaction. The idea is that natural gas can be liquefied, meanwhile gaseous or liquid nitrogen and oxygen are produced in one combined cryogenic system. Cycle simulation and exergy analysis were performed to evaluate the process and thereby reveal the influence of the crucial parameter, i.e., flow rate ratio through two stages expanders β on heat transfer temperature difference, its distribution and consequent exergy loss. Composite curves for the combined hot streams (feeding natural gas and recycled nitrogen) and the cold stream showed the degree of optimization available in this process if appropriate β was designed. The results indicated that increasing β reduces temperature difference and exergy loss in heat exchange process. However, the maximum limit value of β should be confined in terms of minimum temperature difference proposed in heat exchanger design standard and heat exchanger size. The optimal βopt under different operation conditions corresponding to the required minimum temperature differences was investigated.
Abstract: Human activities are increasingly based on the use of remote resources and services, and on the interaction between
remotely located parties that may know little about each other. Mobile agents must be prepared to execute on different hosts with
various environmental security conditions. The aim of this paper is to
propose a trust based mechanism to improve the security of mobile
agents and allow their execution in various environments. Thus, an
adaptive trust mechanism is proposed. It is based on the dynamic interaction between the agent and the environment. Information
collected during the interaction enables generation of an environment
key. This key informs on the host-s trust degree and permits the mobile agent to adapt its execution. Trust estimation is based on
concrete parameters values. Thus, in case of distrust, the source of problem can be located and a mobile agent appropriate behavior can
be selected.
Abstract: The 20th century has brought much development to the practice of Architecture worldwide, and technology has bridged inhabitation limits in many regions of the world with high levels of comfort and conveniences, most times at high costs to the environment. Throughout the globe, the tropical countries are being urbanized at an unprecedented rate and housing has become a major issue worldwide, in light of increased demand and lack of appropriate infra-structure and planning. Buildings and urban spaces designed in tropical cities have mainly adopted external concepts that in most cases do not fit the needs of the inhabitants living in such harsh climatic environment, and when they do, do so at high financial, environmental and cultural costs. Traditional architectural practices can provide valuable understanding on how self-reliance and autonomy of construction can be reinforced in rural-urban tropical environments. From traditional housing knowledge, it is possible to derive lessons for the development of new construction materials that are affordable, environmentally friendly, culturally acceptable and accesible to all.Specifically to the urban context, such solutions are of outmost importance, given the needs to a more democratic society, where access to housing is considered high in the agenda for development. Traditional or rural constructions are also ongoing through extensive changes eventhough they have mostly adopted climate-responsive building practices relying on local resources (with minimum embodied energy) and energy (for comfort and quality of life). It is important to note that many of these buildings can actually be called zero-energy, and hold potential answers to enable transition from high energy, high cost, low comfort urban habitations to zero/low energy habitations with high quality urban livelihood. Increasing access to modern urban lifestyels have also an effect on the aspirations from people in terms of performance, comfort and convenience in terms of their housing and the way it is produced and used. These aspirations are resulting in transitions from localresource dependent habitations- to non-local resource based highenergy urban style habitations. And such transitions are resulting in the habitations becoming increasingly unsuited to the local climatic conditions with increasing discomfort, ill-health, and increased CO2 emissions and local environmental disruption. This research studies one specific transition group in the context of 'water communities' in tropical-equatorial regions: Ribeirinhos housing typology (Amazonas, Brazil). The paper presents the results of a qualitative sustainability assessment of the housing typologies under transition, found at the Ribeirinhos communities.
Abstract: The fault detection and diagnosis of complicated
production processes is one of essential tasks needed to run the process
safely with good final product quality. Unexpected events occurred in
the process may have a serious impact on the process. In this work,
triangular representation of process measurement data obtained in an
on-line basis is evaluated using simulation process. The effect of using
linear and nonlinear reduced spaces is also tested. Their diagnosis
performance was demonstrated using multivariate fault data. It has
shown that the nonlinear technique based diagnosis method produced
more reliable results and outperforms linear method. The use of
appropriate reduced space yielded better diagnosis performance. The
presented diagnosis framework is different from existing ones in that it
attempts to extract the fault pattern in the reduced space, not in the
original process variable space. The use of reduced model space helps
to mitigate the sensitivity of the fault pattern to noise.
Abstract: In this paper a modified version NXM of traditional 5X5 playfair cipher is introduced which enable the user to encrypt message of any Natural language by taking appropriate size of the matrix depending upon the size of the natural language. 5X5 matrix has the capability of storing only 26 characters of English language and unable to store characters of any language having more than 26 characters. To overcome this limitation NXM matrix is introduced which solve this limitation. In this paper a special case of Urdu language is discussed. Where # is used for completing odd pair and * is used for repeating letters.
Abstract: Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.
Abstract: In this paper, a pipelined version of genetic algorithm,
called PLGA, and a corresponding hardware platform are described.
The basic operations of conventional GA (CGA) are made pipelined
using an appropriate selection scheme. The selection operator, used
here, is stochastic in nature and is called SA-selection. This helps
maintaining the basic generational nature of the proposed pipelined
GA (PLGA). A number of benchmark problems are used to compare
the performances of conventional roulette-wheel selection and the
SA-selection. These include unimodal and multimodal functions with
dimensionality varying from very small to very large. It is seen that
the SA-selection scheme is giving comparable performances with
respect to the classical roulette-wheel selection scheme, for all the
instances, when quality of solutions and rate of convergence are considered.
The speedups obtained by PLGA for different benchmarks
are found to be significant. It is shown that a complete hardware
pipeline can be developed using the proposed scheme, if parallel
evaluation of the fitness expression is possible. In this connection
a low-cost but very fast hardware evaluation unit is described.
Results of simulation experiments show that in a pipelined hardware
environment, PLGA will be much faster than CGA. In terms of
efficiency, PLGA is found to outperform parallel GA (PGA) also.
Abstract: Nowadays there are more than thirty maturity models
in different knowledge areas. Maturity model is an area of interest
that contributes organizations to find out where they are in a specific
knowledge area and how to improve it. As Information Resource
Management (IRM) is the concept that information is a major
corporate resource and must be managed using the same basic
principles used to manage other assets, assessment of the current
IRM status and reveal the improvement points can play a critical role
in developing an appropriate information structure in organizations.
In this paper we proposed a framework for information resource
management maturity model (IRM3) that includes ten best practices
for the maturity assessment of the organizations' IRM.
Abstract: This research presents a fuzzy multi-objective model
for a machine selection problem in a flexible manufacturing system
of a tire company. Two main objectives are minimization of an
average machine error and minimization of the total setup time.
Conventionally, the working team uses trial and error in selecting a
pressing machine for each task due to the complexity and constraints
of the problem. So, both objectives may not satisfy. Moreover, trial
and error takes a lot of time to get the final decision. Therefore, in
this research preemptive fuzzy goal programming model is developed
for solving this multi-objective problem. The proposed model can
obtain the appropriate results that the Decision Making (DM) is
satisfied for both objectives. Besides, alternative choice can be easily
generated by varying the satisfaction level. Additionally, decision
time can be reduced by using the model, which includes all
constraints of the system to generate the solutions. A numerical
example is also illustrated to show the effectiveness of the proposed
model.