Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.
Abstract: Virtual Assembly (VA) is one of the key technologies
in advanced manufacturing field. It is a promising application of
virtual reality in design and manufacturing field. It has drawn much
interest from industries and research institutes in the last two decades.
This paper describes a process for integrating an interactive Virtual
Reality-based assembly simulation of a digital mockup with the
CAD/CAM infrastructure. The necessary hardware and software
preconditions for the process are explained so that it can easily be
adopted by non VR experts. The article outlines how assembly
simulation can improve the CAD/CAM procedures and structures;
how CAD model preparations have to be carried out and which
virtual environment requirements have to be fulfilled. The issue of
data transfer is also explained in the paper. The other challenges and
requirements like anti-aliasing and collision detection have also been
explained. Finally, a VA simulation has been carried out for a ball
valve assembly and a car door assembly with the help of Vizard
virtual reality toolkit in a semi-immersive environment and their
performance analysis has been done on different workstations to
evaluate the importance of graphical processing unit (GPU) in the
field of VA.
Abstract: The purpose of this study was to examine the viewpoints in terms of changing distances and levels and thereby, comparatively analyze the visual sensitivity to the elements of the natural views. The questionnaire survey was conducted separately for experts and non-experts. Summing up, it was confirmed that the visual sensitivity to the elements of the same natural views differed significantly depending on subjects' professionalism, changes of the viewpoint levels and distances, while the visual sensitivity to 'openness of visual/view axes' did not differ significantly when only the distances of the viewpoints were varied. In addition, the visual sensitivity to visual/view axes differed between experts and ordinary people when the levels of the viewpoints were varied, while the visual sensitivity to 'damaged natural view resources' differed between two groups when the distances of the viewpoints were varied.
Abstract: In this paper we introduce a novel method for
the characterization of synchronziation and coupling effects
in multivariate time series that can be used for the analysis
of EEG or ECoG signals recorded during epileptic seizures.
The method allows to visualize the spatio-temporal evolution
of synchronization and coupling effects that are characteristic
for epileptic seizures. Similar to other methods proposed for
this purpose our method is based on a regression analysis.
However, a more general definition of the regression together
with an effective channel selection procedure allows to use the
method even for time series that are highly correlated, which
is commonly the case in EEG/ECoG recordings with large
numbers of electrodes. The method was experimentally tested
on ECoG recordings of epileptic seizures from patients with
temporal lobe epilepsies. A comparision with the results from
a independent visual inspection by clinical experts showed
an excellent agreement with the patterns obtained with the
proposed method.
Abstract: In this paper, the authors present architecture of a multi agent consultation system for obesity related problems, which hybrid the technology of an expert system (ES) and an intelligent agent (IA). The strength of the ES which is capable of pulling the expert knowledge is consulted and presented to the end user via the autonomous and friendly pushing environment of the intelligent agent.
Abstract: In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.
Abstract: The requirement to improve software productivity has
promoted the research on software metric technology. There are
metrics for identifying the quality of reusable components but the
function that makes use of these metrics to find reusability of
software components is still not clear. These metrics if identified in
the design phase or even in the coding phase can help us to reduce the
rework by improving quality of reuse of the component and hence
improve the productivity due to probabilistic increase in the reuse
level. CK metric suit is most widely used metrics for the objectoriented
(OO) software; we critically analyzed the CK metrics, tried
to remove the inconsistencies and devised the framework of metrics
to obtain the structural analysis of OO-based software components.
Neural network can learn new relationships with new input data and
can be used to refine fuzzy rules to create fuzzy adaptive system.
Hence, Neuro-fuzzy inference engine can be used to evaluate the
reusability of OO-based component using its structural attributes as
inputs. In this paper, an algorithm has been proposed in which the
inputs can be given to Neuro-fuzzy system in form of tuned WMC,
DIT, NOC, CBO , LCOM values of the OO software component and
output can be obtained in terms of reusability. The developed
reusability model has produced high precision results as expected by
the human experts.
Abstract: In order to explore the relationship of promotion activities, destination attribute and destination image of Vietnam and find possible solutions, this study uses decision system analysis (DSA) method to develop flowcharts based on three rounds of expert interviews. The interviews were conducted with the experts who were confirmed to directly participate or influence on the decision making that drives the promotion of Vietnam tourism process. This study identifies three models and describes specific decisions on promotion activities, destination attributes and destination images. This study finally derives a general model for promoting the Tourism Industrial Service Network (TISN) in Vietnam. This study finds that the coordination with all sectors and industries of tourism to facilitate favorable condition and improving destination attributes in linking with the efficient promotion activities is highly recommended in order to make visitors satisfied and improve the destination image.
Abstract: The International Classification of Primary Care (ICPC), which belongs to the WHO Family of International Classifications (WHO-FIC), has a low granularity, which is convenient for describing general medical practice. However, its lack of specificity makes it useful to be used along with an interface terminology. An international survey has been performed, using a questionnaire sent by email to experts from 25 countries, in order to describe the terminologies interfacing with ICPC. Eleven interface terminologies have been identified, developed in Argentina, Australia, Belgium (2), Canada, Denmark, France, Germany, Norway, South Africa, and The Netherlands. Globally, these systems have been poorly assessed until now.
Abstract: The multi-agent system for processing Bio-signals
will help the medical practitioners to have a standard examination
procedure stored in web server. Web Servers supporting any standard
Search Engine follow all possible combinations of the search
keywords as an input by the user to a Search Engine. As a result, a
huge number of Web-pages are shown in the Web browser. It also
helps the medical practitioner to interact with the expert in the field
his need in order to make a proper judgment in the diagnosis phase
[3].A web server uses a web server plug in to establish and
maintained the medical practitioner to make a fast analysis. If the
user uses the web server client can get a related data requesting their
search. DB agent, EEG / ECG / EMG agents- user placed with
difficult aspects for updating medical information-s in web server.
Abstract: A multi-agent system is developed here to predict
monthly details of the upcoming peak of the 24th solar magnetic
cycle. While studies typically predict the timing and magnitude of
cycle peaks using annual data, this one utilizes the unsmoothed
monthly sunspot number instead. Monthly numbers display more
pronounced fluctuations during periods of strong solar magnetic
activity than the annual sunspot numbers. Because strong magnetic
activities may cause significant economic damages, predicting
monthly variations should provide different and perhaps helpful
information for decision-making purposes. The multi-agent system
developed here operates in two stages. In the first, it produces twelve
predictions of the monthly numbers. In the second, it uses those
predictions to deliver a final forecast. Acting as expert agents, genetic
programming and neural networks produce the twelve fits and
forecasts as well as the final forecast. According to the results
obtained, the next peak is predicted to be 156 and is expected to
occur in October 2011- with an average of 136 for that year.
Abstract: International markets driven forces are changing
continuously, therefore companies need to gain a competitive edge in
such markets. Improving the company's products, processes and
practices is no longer auxiliary. Lean production is a production
management philosophy that consolidates work tasks with minimum
waste resulting in improved productivity. Lean production practices
can be mapped into many production areas. One of these is
Manufacturing Equipment and Technology (MET). Many lean
production practices can be implemented in MET, namely, specific
equipment configurations, total preventive maintenance, visual
control, new equipment/ technologies, production process
reengineering and shared vision of perfection.The purpose of this
paper is to investigate the implementation level of these six practices
in Jordanian industries. To achieve that a questionnaire survey has
been designed according to five-point Likert scale. The questionnaire
is validated through pilot study and through experts review. A sample
of 350 Jordanian companies were surveyed, the response rate was
83%. The respondents were asked to rate the extent of
implementation for each of practices. A relationship conceptual
model is developed, hypotheses are proposed, and consequently the
essential statistical analyses are then performed. An assessment tool
that enables management to monitor the progress and the
effectiveness of lean practices implementation is designed and
presented. Consequently, the results show that the average
implementation level of lean practices in MET is 77%, Jordanian
companies are implementing successfully the considered lean
production practices, and the presented model has Cronbach-s alpha
value of 0.87 which is good evidence on model consistency and
results validation.
Abstract: There are different kinds of online systems on the Internet for people who need support and develop new knowledge. Online communities and Ask the Expert systems are two such systems. In the health care area, the number of users of these systems has increased at a rapid pace. Interactions with medical trained experts take place online, and people with concerns about similar health problems come together to share experiences and advice. The systems are also used as storages and browsed for health information. Over the years, studies have been conducted of the usage of the different systems. However, in what ways the systems can be used together to enhance learning has not been explored. This paper presents results from a study of online health-communities and an Ask the Expert system for people who suffer from overweight. Differences and similarities in regards to posted issues and replies are discussed, and suggestions for a new holistic design of the two systems are presented.
Abstract: Information Technology (IT) projects are always
accompanied by various risks and because of high rate of failure in
such projects, managing risks in order to neutralize or at least
decrease their effects on the success of the project is strongly
essential. In this paper, fuzzy analytical hierarchy process (FAHP) is
exploited as a means of risk evaluation methodology to prioritize and
organize risk factors faced in IT projects. A real case of IT projects, a
project of design and implementation of an integrated information
system in a vehicle producing company in Iran is studied. Related
risk factors are identified and then expert qualitative judgments about
these factors are acquired. Translating these judgments to fuzzy
numbers and using them as an input to FAHP, risk factors are then
ranked and prioritized by FAHP in order to make project managers
aware of more important risks and enable them to adopt suitable
measures to deal with these highly devastative risks.
Abstract: This paper focuses on robust design and optimization
of industrial production wastes. Past literatures were reviewed to case
study Clamason Industries Limited (CIL) - a leading ladder-tops
manufacturer. A painstaking study of the firm-s practices at the shop
floor revealed that Over-production, Waiting time, Excess inventory,
and Defects are the major wastes that are impeding their progress and
profitability. Design expert8 software was used to apply Taguchi
robust design and response surface methodology in order to model,
analyse and optimise the wastes cost in CIL. Waiting time and overproduction
rank first and second in contributing to the costs of wastes
in CIL. For minimal wastes cost the control factors of overproduction,
waiting-time, defects and excess-inventory must be set at
0.30, 390.70, 4 and 55.70 respectively for CIL. The optimal value of
cost of wastes for the months studied was 22.3679. Finally, a
recommendation was made that for the company to enhance their
profitability and customer satisfaction, they must adopt the Shingeo
Shingo-s Single Minute Exchange of Dies (SMED), which will
immediately tackle the waste of waiting by drastically reducing their
setup time.
Abstract: Decisions are regularly made during a project or
daily life. Some decisions are critical and have a direct impact on
project or human success. Formal evaluation is thus required,
especially for crucial decisions, to arrive at the optimal solution
among alternatives to address issues. According to microeconomic
theory, all people-s decisions can be modeled as indifference curves.
The proposed approach supports formal analysis and decision by
constructing indifference curve model from the previous experts-
decision criteria. These knowledge embedded in the system can be
reused or help naïve users select alternative solution of the similar
problem. Moreover, the method is flexible to cope with unlimited
number of factors influencing the decision-making. The preliminary
experimental results of the alternative selection are accurately
matched with the expert-s decisions.
Abstract: The Spiral development model has been used
successfully in many commercial systems and in a good number of
defense systems. This is due to the fact that cost-effective
incremental commitment of funds, via an analogy of the spiral model
to stud poker and also can be used to develop hardware or integrate
software, hardware, and systems. To support adaptive, semantic
collaboration between domain experts and knowledge engineers, a
new knowledge engineering process, called Spiral_OWL is proposed.
This model is based on the idea of iterative refinement, annotation
and structuring of knowledge base. The Spiral_OWL model is
generated base on spiral model and knowledge engineering
methodology. A central paradigm for Spiral_OWL model is the
concentration on risk-driven determination of knowledge engineering
process. The collaboration aspect comes into play during knowledge
acquisition and knowledge validation phase. Design rationales for the
Spiral_OWL model are to be easy-to-implement, well-organized, and
iterative development cycle as an expanding spiral.
Abstract: The aim of this research is to design a collaborative
framework that integrates risk analysis activities into the geospatial
database design (GDD) process. Risk analysis is rarely undertaken
iteratively as part of the present GDD methods in conformance to
requirement engineering (RE) guidelines and risk standards.
Accordingly, when risk analysis is performed during the GDD, some
foreseeable risks may be overlooked and not reach the output
specifications especially when user intentions are not systematically
collected. This may lead to ill-defined requirements and ultimately in
higher risks of geospatial data misuse. The adopted approach consists
of 1) reviewing risk analysis process within the scope of RE and
GDD, 2) analyzing the challenges of risk analysis within the context
of GDD, and 3) presenting the components of a risk-based
collaborative framework that improves the collection of the
intended/forbidden usages of the data and helps geo-IT experts to
discover implicit requirements and risks.
Abstract: This paper proposes the use of Bayesian belief
networks (BBN) as a higher level of health risk assessment for a
dumping site of lead battery smelter factory. On the basis of the
epidemiological studies, the actual hospital attendance records and
expert experiences, the BBN is capable of capturing the probabilistic
relationships between the hazardous substances and their adverse
health effects, and accordingly inferring the morbidity of the adverse
health effects. The provision of the morbidity rates of the related
diseases is more informative and can alleviate the drawbacks of
conventional methods.