Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: The paper represents a reflection on how to select proper indicators to assess the progress of regional contexts towards a knowledge-based society. Taking the first research methodologies elaborated at an international level (World Bank, OECD, etc.) as a reference point, this work intends to identify a set of indicators of the knowledge economy suitable to adequately understand in which manner and to which extent the territorial development dynamics are correlated with the knowledge-base of the considered local society. After a critical survey of the variables utilized within other approaches adopted by international or national organizations, this paper seeks to elaborate a framework of variables, named Regional Knowledge Economy Indicators (ReKEI), necessary to describe the knowledge-based relations of subnational socio-economic contexts. The realization of this framework has a double purpose: an analytical one consisting in highlighting the regional differences in the governance of knowledge based processes, and an operative one consisting in providing some reference parameters for contributing to increasing the effectiveness of those economic policies aiming at enlarging the knowledge bases of local societies.
Abstract: The main objective of this study was to remove and recover Ni, Cu and Fe from a mixed metal system using sodium hypophosphite as a reducing agent and nickel powder as seeding material. The metal systems studied consisted of Ni-Cu, Ni-Fe and Ni-Cu-Fe solutions. A 5 L batch reactor was used to conduct experiments where 100 mg/l of each respective metal was used. It was found that the metals were reduced to their elemental form with removal efficiencies of over 80%. The removal efficiency decreased in the order Fe>Ni>Cu. The metal powder obtained contained between 97-99% Ni and was almost spherical and porous. Size enlargement by aggregation was the dominant particulate process.
Abstract: Cardiovascular diseases, principally atherosclerosis, are responsible for 30% of world deaths. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis.It is increasingly recognized that the initiation and progression of disease and the occurrence of clinical events is a complex interplay between the local biomechanical environment and the local vascular biology. The aim of this study is to investigate the flow behavior through a stenosed artery. A physical experiment was performed using an artery model and blood analogue fluid. An axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. The flow field was measured using particle image velocimetry (PIV). Spherical particles with 20μm diameter were seeded in a water-glycerol-NaCl mixture. Steady flow Reynolds numbers are 250. The area of interest is the region after the stenosis where the flow separation occurs. The velocity field was measured and the velocity gradient was investigated. There was high particle concentration in the recirculation zone. High velocity gradient formed immediately after the stenosis throat created a lift force that enhanced particle migration to the flow separation area.
Abstract: Safer driver behavior promoting is the main goal of this paper. It is a fact that drivers behavior is relatively safer when being monitored. Thus, in this paper, we propose a monitoring system to report specific driving event as well as the potentially aggressive events for estimation of the driving performance. Our driving monitoring system is composed of two parts. The first part is the in-vehicle embedded system which is composed of a GPS receiver, a two-axis accelerometer, radar sensor, OBD interface, and GPRS modem. The design considerations that led to this architecture is described in this paper. The second part is a web server where an adaptive hierarchical fuzzy system is proposed to classify the driving performance based on the data that is sent by the in-vehicle embedded system and the data that is provided by the geographical information system (GIS). Our system is robust, inexpensive and small enough to fit inside a vehicle without distracting the driver.
Abstract: This paper investigates the effect of product substitution in the single-period 'newsboy-type' problem in a fuzzy environment. It is supposed that the single-period problem operates under uncertainty in customer demand, which is described by imprecise terms and modelled by fuzzy sets. To perform this analysis, we consider the fuzzy model for two-item with upward substitution. This upward substitutability is reasonable when the products can be stored according to certain attribute levels such as quality, brand or package size. We show that the explicit consideration of this substitution opportunity increase the average expected profit. Computational study is performed to observe the benefits of product's substitution.
Abstract: Although lots of research work has been done for
human pose recognition, the view-point of cameras is still critical
problem of overall recognition system. In this paper, view-point
insensitive human pose recognition is proposed. The aims of the
proposed system are view-point insensitivity and real-time processing.
Recognition system consists of feature extraction module, neural
network and real-time feed forward calculation. First, histogram-based
method is used to extract feature from silhouette image and it is
suitable for represent the shape of human pose. To reduce the
dimension of feature vector, Principle Component Analysis(PCA) is
used. Second, real-time processing is implemented by using Compute
Unified Device Architecture(CUDA) and this architecture improves
the speed of feed-forward calculation of neural network. We
demonstrate the effectiveness of our approach with experiments on
real environment.
Abstract: An acyclic coloring of a graph G is a coloring of its
vertices such that:(i) no two neighbors in G are assigned the same
color and (ii) no bicolored cycle can exist in G. The acyclic chromatic
number of G is the least number of colors necessary to acyclically
color G. Recently it has been proved that any graph of maximum
degree 5 has an acyclic chromatic number at most 8. In this paper
we present another proof for this result.
Abstract: Increasing demand on the performance of Subsea
Production Systems (SPS) suggests a need for more detailed
investigation of fluid behavior taking place in subsea equipment.
Complete CFD cool down analyses of subsea equipment are very
time demanding. The objective of this paper is to investigate a
Locked CFD approach, which enables significant reduction of the
computational time and at the same time maintains sufficient
accuracy during thermal cool down simulations. The result
comparison of a dead leg simulation using the Full CFD and the three
LCFD-methods confirms the validity of the locked flow field
assumption for the selected case. For the tested case the LCFD
simulation speed up by factor of 200 results in the absolute thermal
error of 0.5 °C (3% relative error), speed up by factor of 10 keeps the
LCFD results within 0.1 °C (0.5 % relative error) comparing to the
Full CFD.
Abstract: In this paper, we proposed the distribution of mesh
normal vector direction as a feature descriptor of a 3D model. A
normal vector shows the entire shape of a model well. The
distribution of normal vectors was sampled in proportion to each
polygon's area so that the information on the surface with less surface
area may be less reflected on composing a feature descriptor in order
to enhance retrieval performance. At the analysis result of ANMRR,
the enhancement of approx. 12.4%~34.7% compared to the existing
method has also been indicated.
Abstract: The mechanical properties of blends consisting of
plasticized poly(vinyl butyral) (PVB) and plasticized poly(vinyl
chloride) (PVC) are studied, in order to evaluate the possibility of
using recycled PVB waste derived from windshields. PVC was
plasticized with 38% of diisononyl phthalate (DINP), while PVB was
plasticized with 28% of triethylene glycol, bis(2-ethylhexanoate)
(3GO). The optimal process conditions for the PVB/PVC blend in 1:1
ratio were determined. Entropy was used in order to theoretically
predict the blends miscibility. The PVB content of each blend
composition used was ranging from zero to 100%. Tensile strength
and strain were tested. In addition, a comparison between recycled
and original PVB, used as constituents of the blend, was performed.
Abstract: Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Abstract: In this paper, a neural network tuned fuzzy controller
is proposed for controlling Multi-Input Multi-Output (MIMO)
systems. For the convenience of analysis, the structure of MIMO
fuzzy controller is divided into single input single-output (SISO)
controllers for controlling each degree of freedom. Secondly,
according to the characteristics of the system-s dynamics coupling, an
appropriate coupling fuzzy controller is incorporated to improve the
performance. The simulation analysis on a two-level mass–spring
MIMO vibration system is carried out and results show the
effectiveness of the proposed fuzzy controller. The performance
though improved, the computational time and memory used is
comparatively higher, because it has four fuzzy reasoning blocks and
number may increase in case of other MIMO system. Then a fuzzy
neural network is designed from a set of input-output training data to
reduce the computing burden during implementation. This control
strategy can not only simplify the implementation problem of fuzzy
control, but also reduce computational time and consume less
memory.
Abstract: Scheduling algorithms are used in operating systems
to optimize the usage of processors. One of the most efficient
algorithms for scheduling is Multi-Layer Feedback Queue (MLFQ)
algorithm which uses several queues with different quanta. The most
important weakness of this method is the inability to define the
optimized the number of the queues and quantum of each queue. This
weakness has been improved in IMLFQ scheduling algorithm.
Number of the queues and quantum of each queue affect the response
time directly. In this paper, we review the IMLFQ algorithm for
solving these problems and minimizing the response time. In this
algorithm Recurrent Neural Network has been utilized to find both
the number of queues and the optimized quantum of each queue.
Also in order to prevent any probable faults in processes' response
time computation, a new fault tolerant approach has been presented.
In this approach we use combinational software redundancy to
prevent the any probable faults. The experimental results show that
using the IMLFQ algorithm results in better response time in
comparison with other scheduling algorithms also by using fault
tolerant mechanism we improve IMLFQ performance.
Abstract: This research was conducted in the Lower Namkam
Irrigation Project situated in the Namkam River Basin in Thailand.
Degradation of groundwater quality in some areas is caused by saline
soil spots beneath ground surface. However, the tail regulated gate
structure on the Namkam River, a lateral stream of the Mekong
River. It is aimed for maintaining water level in the river at +137.5 to
+138.5 m (MSL) and flow to the irrigation canals based on a gravity
system since July 2009. It might leach some saline soil spots from
underground to soil surface if lack of understanding of the
conjunctive surface water and groundwater behaviors. This research
has been conducted by continuously the observing of both shallow
and deep groundwater level and quality from existing observation
wells. The simulation of surface water was carried out using a
hydrologic modeling system (HEC-HMS) to compute the ungauged
side flow catchments as the lateral flows for the river system model
(HEC-RAS). The constant water levels in the upstream of the
operated gate caused a slight rising up of shallow groundwater level
when compared to the water table. However, the groundwater levels
in the confined aquifers remained less impacted than in the shallow
aquifers but groundwater levels in late of wet season in some wells
were higher than the phreatic surface. This causes salinization of the
groundwater at the soil surface and might affect some crops. This
research aims for the balance of water stage in the river and efficient
groundwater utilization in this area.
Abstract: The purpose of our study was to compare spontaneous
re-epithelisation characteristics versus assisted re-epithelisation. In
order to assess re-epithelisation of the injured skin, we have imagined
and designed a burn wound model on Wistar rat skin. Our aim was to
create standardised, easy reproducible and quantifiable skin lesions
involving entire epidermis and superficial dermis. We then have
applied the above mentioned therapeutic strategies to compare
regeneration of epidermis and dermis, local and systemic parameter
changes in different conditions. We have enhanced the reepithelisation
process under a moist atmosphere of a polyurethane
wound dress modified with helium non-thermal plasma, and with the
aid of direct cold-plasma treatment respectively. We have followed
systemic parameters change: hematologic and biochemical
parameters, and local features: oxidative stress markers and histology
of skin in the above mentioned conditions. Re-epithelisation is just a
part of the skin regeneration process, which recruits cellular
components, with the aid of epidermal and dermal interaction via
signal molecules.
Abstract: This paper describes the implementation and testing
of a multichannel active noise control system (ANCS) based on the
filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is
derived from the well-known filtered-x LMS (FXLMS) algorithm
with the aim to improve the rate of convergence of the multichannel
FXLMS algorithm and to reduce its computational load. Laboratory
setup and techniques used to implement this system efficiently are
described in this paper. Experiments performed in order to test the
performance of the FILMS algorithm are discussed and the obtained
results presented.
Abstract: There is a complex situation on the transport environment in the cities of the world. For the analysis and prevention of environmental problems an accurate calculation hazardous substances concentrations at each point of the investigated area is required. In the turbulent atmosphere of the city the wellknown methods of mathematical statistics for these tasks cannot be applied with a satisfactory level of accuracy. Therefore, to solve this class of problems apparatus of mathematical physics is more appropriate. In such models, because of the difficulty as a rule the influence of uneven land surface on streams of air masses in the turbulent atmosphere of the city are not taken into account. In this paper the influence of the surface roughness, which can be quite large, is mathematically shown. The analysis of this problem under certain conditions identified the possibility of areas appearing in the atmosphere with pressure tending to infinity, i.e. so-called "wall effect".
Abstract: The recent advances in computational fluid dynamics
(CFD) can be useful in observing the detailed hemodynamics in
cerebral aneurysms for understanding not only their formation and
rupture but also for clinical evaluation and treatment. However,
important hemodynamic quantities are difficult to measure in vivo. In
the present study, an approximate model of normal middle cerebral
artery (MCA) along with two cases consisting broad and narrow
saccular aneurysms are analyzed. The models are generated in
ANSYS WORKBENCH and transient analysis is performed in
ANSYS-CFX. The results obtained are compared for three cases and
agree well with the available literature.
Abstract: This paper introduces an intelligent system, which can be applied in the monitoring of vehicle speed using a single camera. The ability of motion tracking is extremely useful in many automation problems and the solution to this problem will open up many future applications. One of the most common problems in our daily life is the speed detection of vehicles on a highway. In this paper, a novel technique is developed to track multiple moving objects with their speeds being estimated using a sequence of video frames. Field test has been conducted to capture real-life data and the processed results were presented. Multiple object problems and noisy in data are also considered. Implementing this system in real-time is straightforward. The proposal can accurately evaluate the position and the orientation of moving objects in real-time. The transformations and calibration between the 2D image and the actual road are also considered.