Abstract: Model-based approaches have been applied successfully
to a wide range of tasks such as specification, simulation, testing, and
diagnosis. But one bottleneck often prevents the introduction of these
ideas: Manual modeling is a non-trivial, time-consuming task.
Automatically deriving models by observing and analyzing running
systems is one possible way to amend this bottleneck. To
derive a model automatically, some a-priori knowledge about the
model structure–i.e. about the system–must exist. Such a model
formalism would be used as follows: (i) By observing the network
traffic, a model of the long-term system behavior could be generated
automatically, (ii) Test vectors can be generated from the model,
(iii) While the system is running, the model could be used to diagnose
non-normal system behavior.
The main contribution of this paper is the introduction of a model
formalism called 'probabilistic regression automaton' suitable for the
tasks mentioned above.
Abstract: This paper explores the knowledge and attitude of
women and men in decision making on pap smear screening. This
qualitative study recruited 52 respondents with 44 women and 8 men,
using the purposive sampling with snowballing technique through indepth
interviews. This study demonstrates several key findings:
Female respondents have better knowledge compared to male. Most
of the women perceived that pap smear screening is beneficial and
important, but to proceed with the test is still doubtful. Male
respondents were supportive in terms of sending their spouses to the
health facilities or give more freedom to their wives to choose and
making decision on their own health due to prominent reason that
women know best on their own health. It is expected that the results
from this study will provide useful guideline for healthcare providers
to prepare any action/intervention to provide an extensive education
to improve people-s knowledge and attitude towards pap smear.
Abstract: Support vector machines (SVMs) have shown
superior performance compared to other machine learning techniques,
especially in classification problems. Yet one limitation of SVMs is
the lack of an explanation capability which is crucial in some
applications, e.g. in the medical and security domains. In this paper, a
novel approach for eclectic rule-extraction from support vector
machines is presented. This approach utilizes the knowledge acquired
by the SVM and represented in its support vectors as well as the
parameters associated with them. The approach includes three stages;
training, propositional rule-extraction and rule quality evaluation.
Results from four different experiments have demonstrated the value
of the approach for extracting comprehensible rules of high accuracy
and fidelity.
Abstract: The article investigates how 14- to 15- year-olds build informal conceptions of inferential statistics as they engage in a modelling process and build their own computer simulations with dynamic statistical software. This study proposes four primary phases of informal inferential reasoning for the students in the statistical modeling and simulation process. Findings show shifts in the conceptual structures across the four phases and point to the potential of all of these phases for fostering the development of students- robust knowledge of the logic of inference when using computer based simulations to model and investigate statistical questions.
Abstract: Using the animations video of teaching materials is an
effective learning method. However, we thought that more effective learning method is to produce the teaching video by learners
themselves. The learners who act as the producer must learn and understand well to produce and present video of teaching materials to
others. The purpose of this study is to propose the project based learning (PBL) technique by co-producing video of IT (information
technology) teaching materials. We used the T2V player to produce
the video based on TVML a TV program description language. By
proposed method, we have assigned the learners to produce the
animations video for “National Examination for Information
Processing Technicians (IPA examination)" in Japan, in order to get
them learns various knowledge and skill on IT field. Experimental
result showed that learning effect has occurred at the video production
process that useful for IT personnel resources development.
Abstract: Tourism is a phenomenon respected by the human communities since a long time ago. It has been evoloving continually based on a variety of social and economic needs and with respect to increasingly development of communication and considerable increase of tourist-s number and resulted exchange income has attained much out come such as employment for the communities. or the purpose of tourism development in this zone suitable times and locations need to be specified in the zone for the tourist-s attendance. One of the most important needs of the tourists is the knowledge of climate conditions and suitable times for sightseeing. In this survey, the climate trend condition has been identified for attending the tourists in Isfahan province using the modified tourism climate index (TCI) as well as SPSS, GIS, excel, surfer softwares. This index evoluates systematically the climate conditions for tourism affairs and activities using the monthly maximum mean parameters of daily temperature, daily mean temperature, minimum relative humidity, daily mean relative humidity, precipitation (mm), total sunny hours, wind speed and dust. The results obtaind using kendal-s correlation test show that the months January, February, March, April, May, June, July, August, September, October, November and December are significant and have an increasing trend that indicates the best condition for attending the tourists. S, P, T mean , T max and dust are estimated from 1976-2005 and do kendal-s correlation test again to see which parameter has been effective. Based on the test, we also observed on the effective parameters that the rate of dust in February, March, April, May, June, July, August, October and November is decreasing and precipitation in September and January is increasing and also the radiation rate in May and August is increasing that indicate a better condition of convenience. Maximum temperature in June is also decreasing. Isfahan province has two spring and fall peaks and the best places for tourism are in the north and western areas.
Abstract: Transferring information developed by other peoples is an ordinary event that happens during daily conversations, for example when employees sea each other in the organization, or when they are having lunch together, or attending a meeting, they use to talk about their experience, and discuss about their current projects, and talk about their successes over some specific problems. Despite the potential value of leveraging organizational memory and expertise by using OMS and ER, still small organizations haven-t been able to capitalize on its promised value. Each organization has its internal knowledge management system, in some of organizations the system face the lack of expert people to save their experience in the repository and in another hand on some other organizations there are lots of expert people but the organization doesn-t have the maximum use of their knowledge.
Abstract: Brucellosis is a zoonotic disease; its symptoms and appearances are not exclusive in human and its traditional diagnosis is based on culture, serological methods and conventional PCR. For more sensitive, specific detection and differentiation of Brucella spp., the real time PCR method is recommended. This research has performed to determine the presence and prevalence of Brucella spp. and differentiation of Brucella abortus and Brucella melitensis in house mouse (Mus musculus) in west of Iran. A TaqMan analysis and single-step PCR was carried out in total 326 DNA of Mouse's spleen samples. From the total number of 326 samples, 128 (39.27%) gave positive results for Brucella spp. by conventional PCR, also 65 and 32 out of the 128 specimens were positive for B. melitensis, B. abortus, respectively. These results indicate a high presence of this pathogen in this area and that real time PCR is considerably faster than current standard methods for identification and differentiation of Brucella species. To our knowledge, this study is the first prevalence report of direct identification and differentiation of B. abortus and B. melitensis by real time PCR in mouse tissue samples in Iran.
Abstract: Firms have invested heavily in knowledge
management (KM) with the aim to build a knowledge capability and
use it to achieve a competitive advantage. Research has shown,
however, that not all knowledge management projects succeed. Some
studies report that about 84% of knowledge management projects
fail. This paper has integrated studies on the impediments to
knowledge management into a theoretical framework. Based on this
framework, five cases documenting failed KM initiatives were
analysed. The analysis gave us a clear picture about why certain KM
projects fail. The high failure rate of KM can be explained by the
gaps that exist between users and management in terms of KM
perceptions and objectives
Abstract: This study aims at investigating the empirical
relationships between risk preference, internet preference, and
internet knowledge which are known as user characteristics, in
addition to perceived risk of the customers on the internet purchase
intention. In order to test the relationships between the variables of
model 174, a questionnaire was collected from the students with
previous online experience. For the purpose of data analysis,
confirmatory factor analysis (CFA) and structural equation model
(SEM) was used.
Test results show that the perceived risk affects the internet
purchase intention, and increase or decrease of perceived risk
influences the purchase intention when the customer does the internet
shopping. Other factors such as internet preference, knowledge of the
internet, and risk preference affect the internet purchase intention.
Abstract: In this paper, we propose a novel spatiotemporal fuzzy
based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership
functions. In this algorithm median filter is used to suppress noise.
Experimental results show when the images are corrupted by highdensity
Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing
noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very
adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our
proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.
Abstract: A self-association model has been used to understand
the concentration dependence of free energy of mixing (GM), heat of
mixing (HM), entropy of mixing (SM), activity (a) and microscopic
structures, such as concentration fluctuation in long wavelength limit
(Scc(0)) and Warren-Cowley short range order parameter ( 1
α )for Cu-
Tl molten alloys at 1573K. A comparative study of surface tension of
the alloys in the liquid state at that temperature has also been carried
out theoretically as function of composition in the light of Butler-s
model, Prasad-s model and quasi-chemical approach. Most of the
computed thermodynamic properties have been found in agreement
with the experimental values. The analysis reveals that the Cu-Tl
molten alloys at 1573K represent a segregating system at all
concentrations with moderate interaction. Surface tensions computed
from different approaches have been found to be comparable to each
other showing increment with the composition of copper.
Abstract: Knowledge sharing enables the information or
knowledge to be transmitted from one source to another. This paper
demonstrates the needs of having the online book catalogue which
can be used to facilitate disseminating information on textbook used
in the university. This project is aimed to give access to the students
and lecturers to the list of books in the bookstore and at the same
time to allow book reviewing without having to visit the bookstore
physically. Research is carried out according to the boundaries which
accounts to current process of new book purchasing, current system
used by the bookstore and current process the lecturers go through
for reviewing textbooks. The questionnaire is used to gather the
requirements and it is distributed to 100 students and 40 lecturers.
This project has enabled the improvement of a manual process to be
carried out automatically, through a web based platform. It is shown
based on the user acceptance survey carried out that target groups
found that this web service is feasible to be implemented in
Universiti Teknologi PETRONAS (UTP), and they have shown
positive signs of interest in utilizing it in the future.
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: Paper presents knowledge about types of test in area
of materials properties of selected methods of rapid prototyping
technologies. In today used rapid prototyping technologies for
production of models and final parts are used materials in initial state
as solid, liquid or powder material structure. In solid state are used
various forms such as pellets, wire or laminates. Basic range
materials include paper, nylon, wax, resins, metals and ceramics. In
Fused Deposition Modeling (FDM) rapid prototyping technology are
mainly used as basic materials ABS (Acrylonitrile Butadiene
Styrene), polyamide, polycarbonate, polyethylene and polypropylene.
For advanced FDM applications are used special materials as silicon
nitrate, PZT (Piezoceramic Material - Lead Zirconate Titanate),
aluminium oxide, hydroxypatite and stainless steel.
Abstract: Knowledge capabilities are increasingly important for
the innovative technology enterprises to enhance the business
performance in terms of product competitiveness, innovation and
sales. Recognition of the company capability by auditing allows them
to further pursue advancement, strategic planning and hence gain
competitive advantages. This paper attempts to develop an
Organizations- Knowledge Capabilities Assessment (OKCA) method
to assess the knowledge capabilities of technology companies. The
OKCA is a questionnaire-based assessment tool which has been
developed to uncover the impact of various knowledge capabilities on
different organizational performance. The collected data is then
analyzed to find out the crucial elements for different technological
companies. Based on the results, innovative technology enterprises are
able to recognize the direction for further improvement on business
performance and future development plan. External environmental
factors affecting organization performance can be found through the
further analysis of some selected reference companies.
Abstract: 20 years of dentistry was a period of transition from
communist to market economy but Romanian doctors have
insufficient management knowledge. Recently, the need for modern
management has increased due to technologies and superior materials
appearance, as patient-s demands.
Research goal is to increase efficiency by evaluating dental
medical office cost categories in real pricing procedures.
Empirical research is based on guided study that includes
information about the association between categories of cost
perception and therapeutic procedures commonly used in dental
offices.
Due to the obtained results to identify all the labours that make up
a settled procedure costs were determined for each procedure.
Financial evaluation software was created with the main functions:
introducing and maintaining patient records, treatment and
appointments made, procedures cost and monitoring office
productivity.
We believe that the study results can significantly improve the
financial management of dental offices, increasing the effectiveness
and quality of services.
Abstract: After reporting a literature review on Customer
Relationship Management (CRM) and knowledge management, some
important issued arise, in particular related to the lack of success of
CRM strategies implementation. The paper contributes to this
proposing an integrated model of CRM success taking into account
complementary factors such as organizational factors, technology,
knowledge management and customer orientation.
Abstract: Nowadays predicting political risk level of country
has become a critical issue for investors who intend to achieve
accurate information concerning stability of the business
environments. Since, most of the times investors are layman and
nonprofessional IT personnel; this paper aims to propose a
framework named GECR in order to help nonexpert persons to
discover political risk stability across time based on the political
news and events.
To achieve this goal, the Bayesian Networks approach was
utilized for 186 political news of Pakistan as sample dataset.
Bayesian Networks as an artificial intelligence approach has been
employed in presented framework, since this is a powerful technique
that can be applied to model uncertain domains. The results showed
that our framework along with Bayesian Networks as decision
support tool, predicted the political risk level with a high degree of
accuracy.
Abstract: The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.