Abstract: In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.
Abstract: The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.
Abstract: Generation of electricity from coal has increased over
the years in the United States and around the world. Burning of coal
results in annual production of upwards of 100 millions tons (United
States only) of coal combustion products (CCPs). Only about a third
of these products are being used to create new products while the
remainder goes to landfills. Application of CCPs mixed with
composted organic materials onto soil can improve the soil-s
physico-chemical conditions and provide essential plant nutritients.
Our objective was to create plant growth media utilizing CCPs and
compost in way which maximizes the use of these products and, at
the same time, maintain good plant growth. Media were formulated
by adding composted organic matter (COM) to CCPs at ratios
ranging from 2:8 to 8:2 (v/v). The quality of these media was
evaluated by measuring their physical and chemical properties and
their effect on plant growth. We tested the media by 1) measuring
their physical and chemical properties and 2) the growth of three
plant species in the experimental media: wheat (Triticum sativum),
tomato (Lycopersicum esculentum) and marigold (Tagetes patula).
We achieved significantly (p < 0.001) higher growth (7-130%) in the
experimental media containing CCPs compared to a commercial mix.
The experimental media supplied adequate plant nutrition as no
fertilization was provided during the experiment. Based on the
results, we recommend the use of CCPs and composts for the
creation of plant growth media.
Abstract: Horizontal platform system (HPS) is popularly applied
in offshore and earthquake technology, but it is difficult and
time-consuming for regulation. In order to understand the nonlinear
dynamic behavior of HPS and reduce the cost when using it, this paper
employs differential transformation method to study the bifurcation
behavior of HPS. The numerical results reveal a complex dynamic
behavior comprising periodic, sub-harmonic, and chaotic responses.
Furthermore, the results reveal the changes which take place in the
dynamic behavior of the HPS as the external torque is increased.
Therefore, the proposed method provides an effective means of
gaining insights into the nonlinear dynamics of horizontal platform
system.
Abstract: This paper presents the analysis of similarity between local decisions, in the process of alphanumeric hand-prints classification. From the analysis of local characteristics of handprinted numerals and characters, extracted by a zoning method, the set of classification decisions is obtained and the similarity among them is investigated. For this purpose the Similarity Index is used, which is an estimator of similarity between classifiers, based on the analysis of agreements between their decisions. The experimental tests, carried out using numerals and characters from the CEDAR and ETL database, respectively, show to what extent different parts of the patterns provide similar classification decisions.
Abstract: Performance of vehicle depends on driving patterns
and vehicle drive train configuration. Driving patterns depends on
traffic condition, road condition and driver behavior. HEV design is
carried out under certain constrain like vehicle operating range,
acceleration, decelerations, maximum speed and road grades which
are directly related to the driving patterns. Therefore the detailed
study on HEV performance over a different drive cycle is required
for selection and sizing of HEV components. A simple hardware is
design to measured velocity v/s time profile of the vehicle by
operating vehicle on Indian roads under real traffic conditions. To
size the HEV components, a detailed dynamic model of the vehicle is
developed considering the effect of inertia of rotating components
like wheels, drive chain, engine and electric motor. Using vehicle
model and different Indian drive cycles data, total tractive power
demanded by vehicle and power supplied by individual components
has been calculated.Using above information selection and estimation
of component sizing for HEV is carried out so that HEV performs
efficiently under hostile driving condition. Complete analysis is
carried out in LABVIEW.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: Voltage stability has become an important issue to many power systems around the world due to the weak systems and long line on power system networks. In this paper, MATLAB load flow program is applied to obtain the weak points in the system combined with finding the voltage stability limit. The maximum permissible loading of a system, within the voltage stability limit, is usually determined. The methods for varying tap ratio (using tap changing transformer) and applying different values of shunt capacitor injection to improve the voltage stability within the limit are also provided.
Abstract: In this work, effects of catalysts (TiO2, and Nb2O5) were investigated on the hydrogen desorption of Mg(BH4)2. LiBH4 and MgCl2 with 2:1 molar ratio were mixed by using ball milling to prepare Mg(BH4)2. The desorption behaviors were measured by thermo-volumetric apparatus. The hydrogen desorption capacity of the mixed sample milled for 2 h was 4.78 wt% with a 2-step released. The first step occurred at 214 °C and the second step appeared at 374 °C. The addition of 16 wt% Nb2O5 decreased the desorption temperature in the second step about 66 °C and increased the hydrogen desorption capacity to 4.86 wt% hydrogen. The addition of TiO2 also improved the desorption temperature in the second step and the hydrogen desorption capacity. It decreased the desorption temperature about 71°C and showed a high amount of hydrogen, 5.27 wt%, released from the mixed sample. The hydrogen absorption after desorption of Mg(BH4)2 was also studied under 9.5 MPa and 350 °C for 12 h.
Abstract: This paper presents an analytical method to solve
governing consolidation parabolic partial differential equation (PDE)
for inelastic porous Medium (soil) with consideration of variation of
equation coefficient under cyclic loading. Since under cyclic loads,
soil skeleton parameters change, this would introduce variable
coefficient of parabolic PDE. Classical theory would not rationalize
consolidation phenomenon in such condition. In this research, a
method based on time space mapping to a virtual time space along
with superimposing rule is employed to solve consolidation of
inelastic soils in cyclic condition. Changes of consolidation
coefficient applied in solution by modification of loading and
unloading duration by introducing virtual time. Mapping function is
calculated based on consolidation partial differential equation results.
Based on superimposing rule a set of continuous static loads in
specified times used instead of cyclic load. A set of laboratory
consolidation tests under cyclic load along with numerical
calculations were performed in order to verify the presented method.
Numerical solution and laboratory tests results showed accuracy of
presented method.
Abstract: The lecture represents significant advances in
understanding of the transfer processes mechanism in turbulent
separated flows. Based upon experimental data suggesting the
governing role of generated local pressure gradient that takes place in
the immediate vicinity of the wall in separated flow as a result of
intense instantaneous accelerations induced by large-scale vortex
flow structures similarity laws for mean velocity and temperature and
spectral characteristics and heat and mass transfer law for turbulent
separated flows have been developed. These laws are confirmed by
available experimental data. The results obtained were employed for
analysis of heat and mass transfer in some very complex processes
occurring in technological applications such as impinging jets, heat
transfer of cylinders in cross flow and in tube banks, packed beds
where processes manifest distinct properties which allow them to be
classified under turbulent separated flows. Many facts have got an
explanation for the first time.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: Process planning and production scheduling play
important roles in manufacturing systems. In this paper a multiobjective
mixed integer linear programming model is presented for
the integrated planning and scheduling of multi-product. The aim is
to find a set of high-quality trade-off solutions. This is a
combinatorial optimization problem with substantially large solution
space, suggesting that it is highly difficult to find the best solutions
with the exact search method. To account for it, a PSO-based
algorithm is proposed by fully utilizing the capability of the
exploration search and fast convergence. To fit the continuous PSO
in the discrete modeled problem, a solution representation is used in
the algorithm. The numerical experiments have been performed to
demonstrate the effectiveness of the proposed algorithm.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.
Abstract: Airbag deployment has been known to be responsible
for huge death, incidental injuries and broken bones due to low crash
severity and wrong deployment decisions. Therefore, the authorities
and industries have been looking for more innovative and intelligent
products to be realized for future enhancements in the vehicle safety
systems (VSSs). Although the VSSs technologies have advanced
considerably, they still face challenges such as how to avoid
unnecessary and untimely airbag deployments that can be hazardous
and fatal. Currently, most of the existing airbag systems deploy
without regard to occupant size and position. As such, this paper will
focus on the occupant and crash sensing performances due to frontal
collisions for the new breed of so called smart airbag systems. It
intends to provide a thorough discussion relating to the occupancy
detection, occupant size classification, occupant off-position
detection to determine safe distance zone for airbag deployment,
crash-severity analysis and airbag decision algorithms via a computer
modeling. The proposed system model consists of three main
modules namely, occupant sensing, crash severity analysis and
decision fusion. The occupant sensing system module utilizes the
weight sensor to determine occupancy, classify the occupant size,
and determine occupant off-position condition to compute safe
distance for airbag deployment. The crash severity analysis module is
used to generate relevant information pertinent to airbag deployment
decision. Outputs from these two modules are fused to the decision
module for correct and efficient airbag deployment action. Computer
modeling work is carried out using Simulink, Stateflow,
SimMechanics and Virtual Reality toolboxes.
Abstract: The purpose of this research was to study the
influence of learning efficiency on local accountants’ job
performance effectiveness. This paper drew upon the survey data
collected from 335 local accountants survey conducted at Nakhon
Ratchasima province, Thailand. The statistics utilized in this paper
included percentage, mean, standard deviation, and regression
analysis. The findings revealed that the majority of samples were
between 31-40 years old, married, held an undergraduate degree, and
had an average income between 10,000-15,000 baht. The majority of
respondents had less than five years of accounting experience and
worked for local administrations. The overall learning efficiency
score was in the highest level while the local accountants’ job
performance effectiveness score was also in the high level. The
hypothesis testing’s result disclosed that learning efficiency factors
which were knowledge, Skill, and Attitude had an influence on local
accountants’ job the performance effectiveness.
Abstract: This study was conducted to evaluate the effects of
gibberellic acid and 2,4- dichlorophenoxyacetic acid on flower
number, fruit growth and fruit quality of wax apple. GA3 and 2,4-D
were applied at small bud and petal fall stage. Number of flower,
fruit set, fruit drop, fruit crack, fruit growth and fruit quality were
recorded. Results indicated that spraying with 10 ppm GA3 had the
best results in number of flower. GA3 spray at 30 ppm gave the
faster rate of fruit growth than the other treatments. Fruit set, fruit
size as well as fruit weight markedly improved by spraying 30 ppm
GA3, followed by 10 ppm GA3 compared to untreated control.
Moreover, spray GA3 at 30 ppm was the most effective and
increased total soluble solids, reduced titratable acidity and fruit
drop. On the other hand, it was noticed that with 10 ppm 2,4-D
application also enhanced the fruit growth rate, improved
physiological and biochemical characters of fruit compared to
untreated control. It was concluded that both GA3 and 2,4-D spray
have positive effects on fruit development, reduced fruit drop, fruit
crack and improved fruit quality of wax apple under field conditions.
Abstract: The increments of aromatic structures are widely used to monitor the degree of humification. Compost derived from mix manures mixed with agricultural wastes was studied. The compost collected at day 0, 7, 14, 21, 28, 35, 49, 77, 91, 105, and 119 was divided into 3 stages, initial stage at day 0, thermophilic stage during day 1-48, and mature stage during day 49-119. The change of highest absorptions at wavelength range between 210-235 nm during day 0- 49 implied that small molecules such as nitrates and carboxylic occurred faster than the aromatic molecules that were found at wavelength around 280 nm. The ratio of electron-transfer band at wavelength 253 nm by the benzonoid band at wavelength 230 nm (E253/E230) also gradually increased during the fermenting period indicating the presence of O-containing functional groups. This was in agreement with the shift change from aliphatic to aromatic structures as shown by the relationship with C/N and H/C ratios (r = - 0.631 and -0.717, p< 0.05) since both were decreasing. Although the amounts of humic acid (HA) were not different much during the humification process, the UV spectral deconvolution showed better qualitative characteristics to help in determining the compost quality. From this study, the compost should be used at day 49 and should not be kept longer than 3 months otherwise the quality of HA would decline regardless of the amounts of HA that might be rising. This implied that other processes, such as mineralization had an influence on the humification process changing HA-s structure and its qualities.
Abstract: Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.