Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: Measurement and the following evaluation of
performance represent important part of management. The paper
focuses on indicators as the basic elements of performance
measurement system. It emphasizes a necessity of searching
requirements for quality indicators so that they can become part of
the useful system. It introduces standpoints for a systematic dividing
of indicators so that they have as high as possible informative value
of background sources for searching, analysis, designing and using of
indicators. It draws attention to requirements for indicators' quality
and at the same it deals with some dangers decreasing indicator's
informative value. It submits a draft of questions that should be
answered at the construction of indicator. It is obvious that particular
indicators need to be defined exactly to stimulate the desired
behavior in order to attain expected results. In the enclosure a
concrete example of the defined indicator in the concrete conditions
of a small firm is given. The authors of the paper pay attention to the
fact that a quality indicator makes it possible to get to the basic
causes of the problem and include the established facts into the
company information system. At the same time they emphasize that
developing of a quality indicator is a prerequisite for the utilization
of the system of measurement in management.
Abstract: In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Abstract: Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: Buyer coalition with a combination of items is a group of buyers joining together to purchase a combination of items with a larger discount. The primary aim of existing buyer coalition with a combination of items research is to generate a large total discount. However, the aim is hard to achieve because this research is based on the assumption that each buyer completely knows other buyers- information or at least one buyer knows other buyers- information in a coalition by exchange of information. These assumption contrast with the real world environment where buyers join a coalition with incomplete information, i.e., they concerned only with their expected discounts. Therefore, this paper proposes a new buyer community coalition formation with a combination of items scheme, called the Community Compromised Combinatorial Coalition scheme, under such an environment of incomplete information. In order to generate a larger total discount, after buyers who want to join a coalition propose their minimum required saving, a coalition structure that gives a maximum total retail prices is formed. Then, the total discount division of the coalition is divided among buyers in the coalition depending on their minimum required saving and is a Pareto optimal. In mathematical analysis, we compare concepts of this scheme with concepts of the existing buyer coalition scheme. Our mathematical analysis results show that the total discount of the coalition in this scheme is larger than that in the existing buyer coalition scheme.
Abstract: The modern queueing theory is one of the powerful
tools for a quantitative and qualitative analysis of communication systems, computer networks, transportation systems, and many other technical systems. The paper is designated to the analysis of queueing
systems, arising in the networks theory and communications theory
(called open queueing network). The authors of this research in the
sphere of queueing theory present the theorem about the law of the iterated logarithm (LIL) for the queue length of a customers in open
queueing network and its application to the mathematical model of
the open message switching system.
Abstract: Network exchange is now widely used. However, it still
cannot avoid the problems evolving from network exchange. For
example. A buyer may not receive the order even if he/she makes the
payment. For another example, the seller possibly get nothing even
when the merchandise is sent. Some studies about the fair exchange
have proposed protocols for the design of efficiency and exploited the
signature property to specify that two parties agree on the exchange.
The information about purchased item and price are disclosed in
this way. This paper proposes a new fair network payment protocol
with off-line trusted third party. The proposed protocol can protect
the buyers- purchase message from being traced. In addition, the
proposed protocol can meet the proposed requirements. The most
significant feature is Non-transfer property we achieved.
Abstract: Indigenous Knowledge (IK) has many social and
economic benefits. However, IK is at the risk of extinction due to the
difficulties to preserve it as most of the IK largely remains
undocumented. This study aims to design a model of the factors
affecting the adoption of Information and Communication
Technologies (ICTs) for the preservation of IK. The proposed model
is based on theoretical frameworks on ICT adoption. It was designed
following a literature review of ICT adoption theories for households,
and of the factors affecting ICT adoption for IK. The theory that
fitted to the best all factors was then chosen as the basis for the
proposed model. This study found that the Model of Adoption of
Technology in Households (MATH) is the most suitable theoretical
framework for modeling ICT adoption factors for the preservation of
IK.
Abstract: This contribution deals with the relationship between
communication effectiveness and the extent of communication
among organizational units. To facilitate communication between
employees and to increase the level of understanding, the knowledge
of communication tools is necessary. Recent experience has shown
that personal communication is critical for smooth running of
companies and cannot be fully replaced by any form of technical
communication devices.
Below are presented the outcomes of the research on the
relationship between the extent of communication among
organisational units and its efficiency.
Abstract: Ground-level tropospheric ozone is one of the air
pollutants of most concern. It is mainly produced by photochemical
processes involving nitrogen oxides and volatile organic compounds
in the lower parts of the atmosphere. Ozone levels become
particularly high in regions close to high ozone precursor emissions
and during summer, when stagnant meteorological conditions with
high insolation and high temperatures are common.
In this work, some results of a study about urban ozone
distribution patterns in the city of Badajoz, which is the largest and
most industrialized city in Extremadura region (southwest Spain) are
shown. Fourteen sampling campaigns, at least one per month, were
carried out to measure ambient air ozone concentrations, during
periods that were selected according to favourable conditions to
ozone production, using an automatic portable analyzer.
Later, to evaluate the ozone distribution at the city, the measured
ozone data were analyzed using geostatistical techniques. Thus, first,
during the exploratory analysis of data, it was revealed that they were
distributed normally, which is a desirable property for the subsequent
stages of the geostatistical study. Secondly, during the structural
analysis of data, theoretical spherical models provided the best fit for
all monthly experimental variograms. The parameters of these
variograms (sill, range and nugget) revealed that the maximum
distance of spatial dependence is between 302-790 m and the
variable, air ozone concentration, is not evenly distributed in reduced
distances. Finally, predictive ozone maps were derived for all points
of the experimental study area, by use of geostatistical algorithms
(kriging). High prediction accuracy was obtained in all cases as
cross-validation showed. Useful information for hazard assessment
was also provided when probability maps, based on kriging
interpolation and kriging standard deviation, were produced.
Abstract: Bacterial magnetic nanoparticles have great useful potential in biotechnological and biomedical applications. In this study, a liquid growth medium was modified for cultivation a fastidious magnetotactic bacterium that has been isolated from Anzali
lagoon, Iran in our previous research. These modifications include
change in vitamin, mineral, carbon sources and etcetera. In our
experience, the serum bottles and designed air-tight laboratory bottles
were used to create microaerobic conditions in order to development
of a method for scale-up experiment. This information may serve as a
guide to green chemistry based biological protocols for the synthesis
of magnetic nanoparticles with control over the chemical
composition, morphology and size.
Abstract: Internet is largely composed of textual contents and a
huge volume of digital contents gets floated over the Internet daily.
The ease of information sharing and re-production has made it
difficult to preserve author-s copyright. Digital watermarking came
up as a solution for copyright protection of plain text problem after
1993. In this paper, we propose a zero text watermarking algorithm
based on occurrence frequency of non-vowel ASCII characters and
words for copyright protection of plain text. The embedding
algorithm makes use of frequency non-vowel ASCII characters and
words to generate a specialized author key. The extraction algorithm
uses this key to extract watermark, hence identify the original
copyright owner. Experimental results illustrate the effectiveness of
the proposed algorithm on text encountering meaning preserving
attacks performed by five independent attackers.
Abstract: One part of the total employee-s reward is apart from basic wages or salary, employee-s benefits and intangible elements also so called contingent (variable) pay. Contingent pay is connected to performance, contribution, capcompetency or skills of individual employees, and to team-s or company-wide performance or to combination of few of the mentioned possibilities. Main aim of this article is to define, based on available information, contingent pay, describe reasons for its implementation and arguments for and against this type of remuneration, but also bring information not only about its extent and level of utilization by organizations of the Czech Republic operating in the field of environmental protection, but also mention their practical experience with this type of remuneration.
Abstract: A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.
Abstract: The objective of this paper is to a design of pattern
classification model based on the back-propagation (BP) algorithm for
decision support system. Standard BP model has done full connection
of each node in the layers from input to output layers. Therefore, it
takes a lot of computing time and iteration computing for good
performance and less accepted error rate when we are doing some
pattern generation or training the network.
However, this model is using exclusive connection in between
hidden layer nodes and output nodes. The advantage of this model is
less number of iteration and better performance compare with standard
back-propagation model. We simulated some cases of classification
data and different setting of network factors (e.g. hidden layer number
and nodes, number of classification and iteration). During our
simulation, we found that most of simulations cases were satisfied by
BP based using exclusive connection network model compared to
standard BP. We expect that this algorithm can be available to
identification of user face, analysis of data, mapping data in between
environment data and information.
Abstract: A number of competing methodologies have been developed
to identify genes and classify DNA sequences into coding
and non-coding sequences. This classification process is fundamental
in gene finding and gene annotation tools and is one of the most
challenging tasks in bioinformatics and computational biology. An
information theory measure based on mutual information has shown
good accuracy in classifying DNA sequences into coding and noncoding.
In this paper we describe a species independent iterative
approach that distinguishes coding from non-coding sequences using
the mutual information measure (MIM). A set of sixty prokaryotes is
used to extract universal training data. To facilitate comparisons with
the published results of other researchers, a test set of 51 bacterial
and archaeal genomes was used to evaluate MIM. These results
demonstrate that MIM produces superior results while remaining
species independent.
Abstract: In this study, a system of encryption based on chaotic
sequences is described. The system is used for encrypting digital
image data for the purpose of secure image transmission. An image
secure communication scheme based on Logistic map chaotic
sequences with a nonlinear function is proposed in this paper.
Encryption and decryption keys are obtained by one-dimensional
Logistic map that generates secret key for the input of the nonlinear
function. Receiver can recover the information using the received
signal and identical key sequences through the inverse system
technique. The results of computer simulations indicate that the
transmitted source image can be correctly and reliably recovered by
using proposed scheme even under the noisy channel. The
performance of the system will be discussed through evaluating the
quality of recovered image with and without channel noise.
Abstract: With the approaching of digital era, various interactive
service platforms and systems support human beings- needs in lives by
different contents and measures. Design strategies have gradually
turned from function-based to user-oriented, and are often customized.
In other words, how designers include users- value reaction in creation
becomes the goal. Creative design service of interior design requires
positive interaction and communication to allow users to obtain full
design information, recognize the style and process of personal needs,
develop creative service design, lower communication time and cost
and satisfy users- sense of achievement. Thus, by constructing a
co-design method, based on the communication between interior
designers and users, this study recognizes users- real needs and
provides the measure of co-design for designers and users.
Abstract: In the current Grid environment, efficient workload
management presents a significant challenge, for which there are
exorbitant de facto standards encompassing resource discovery,
brokerage, and data transfer, among others. In addition, the real-time
resource status, essential for an optimal resource allocation strategy,
is often not readily accessible. To address these issues and provide a
cleaner abstraction of the Grid with the potential of generalizing into
arbitrary resource-sharing environment, this paper proposes a new
Condor-based pilot mechanism applied in the PanDA architecture,
PanDA-PF WMS, with the goal of providing a more generic yet
efficient resource allocating strategy. In this architecture, the PanDA
server primarily acts as a repository of user jobs, responding to pilot
requests from distributed, remote resources. Scheduling decisions are
subsequently made according to the real-time resource information
reported by pilots. Pilot Factory is a Condor-inspired solution for a
scalable pilot dissemination and effectively functions as a resource
provisioning mechanism through which the user-job server, PanDA,
reaches out to the candidate resources only on demand.