Abstract: To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.
Abstract: The sequence Analyze, Design, Develop, Implement, and Evaluate (ADDIE) provides a powerful methodology for designing computer-based educational materials. Helping students to understand this design process sequence may be achieved by providing them with direct, guided experience. This article examines such help and guidance and the overall learning process from a student-s personal experience.
Abstract: Machine-understandable data when strongly
interlinked constitutes the basis for the SemanticWeb. Annotating
web documents is one of the major techniques for creating metadata
on the Web. Annotating websites defines the containing data in a
form which is suitable for interpretation by machines. In this paper,
we present a new approach to annotate websites and documents by
promoting the abstraction level of the annotation process to a
conceptual level. By this means, we hope to solve some of the
problems of the current annotation solutions.
Abstract: Fuzzy controllers are potential candidates for the
control of nonlinear, time variant and also complicated systems. Anti
lock brake system (ABS) which is a nonlinear system, may not be
easily controlled by classical control methods. An intelligent Fuzzy
control method is very useful for this kind of nonlinear system. A
typical antilock brake system (ABS) by sensing the wheel lockup,
releases the brakes for a short period of time, and then reapplies again
the brakes when the wheel spins up. In this paper, an intelligent fuzzy
ABS controller is designed to adjust slipping performance for variety
of roads. There are tow major sections in the proposing control
system. First section consists of tow Fuzzy-Logic Controllers (FLC)
providing optimal brake torque for both front and rear wheels.
Second section which is also a FLC provides required amount of slip
and torque references properties for different kind of roads.
Simulation results of our proposed intelligent ABS for three different
kinds of road show more reliable and better performance in compare
with two other break systems.
Abstract: This paper proposes two types of non-isolated
direct AC-DC converters. First, it shows a buck-boost
converter with an H-bridge, which requires few components
(three switches, two diodes, one inductor and one capacitor) to
convert AC input to DC output directly. This circuit can handle
a wide range of output voltage. Second, a direct AC-DC buck
converter is proposed for lower output voltage applications.
This circuit is analyzed with output voltage of 12V. We
describe circuit topologies, operation principles and simulation
results for both circuits.
Abstract: A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.
Abstract: Protecting is the sources of drinking water is the first
barrier of contamination of drinking water. The Feitsui Reservoir
watershed of Taiwan supplies domestic water for around 5 million
people in the Taipei metropolitan area. Understanding the spatial
patterns of water quality trends in this watershed is an important
agenda for management authorities. This study examined 7 sites in the
watershed for water quality parameters regulated in the standard for
drinking water source. The non-parametric seasonal Mann-Kendall-s
test was used to determine significant trends for each parameter.
Significant trends of increasing pH occurred at the sampling station in
the uppermost stream watershed, and in total phosphorus at 4 sampling
stations in the middle and downstream watershed. Additionally, the
multi-scale land cover assessment and average land slope were used to
explore the influence on the water quality in the watershed. Regression
models for predicting water quality were also developed.
Abstract: This research attempts to explore gaps in Information
Systems (IS) and innovation literatures by developing a model of
Information Technology (IT) capability in enabling innovation. The
research was conducted by using semi-structured interview with six
innovators in business consulting, financial, healthcare and academic
organizations. The interview results suggest four elements of ITenabled
innovation capability which are information (ability to
capture ideas and knowledge), connectivity (ability to bridge
geographical boundary and mobilize human resources),
communication (ability to attain and engage relationships between
human resources) and transformation (ability to change the functions
and process integrations) in defining IT-enabled innovation platform.
The results also suggests innovators- roles and IT capability.
Abstract: In this paper, we propose a robust disease detection
method, called adaptive orientation code matching (Adaptive OCM),
which is developed from a robust image registration algorithm:
orientation code matching (OCM), to achieve continuous and
site-specific detection of changes in plant disease. We use two-stage
framework for realizing our research purpose; in the first stage,
adaptive OCM was employed which could not only realize the
continuous and site-specific observation of disease development, but
also shows its excellent robustness for non-rigid plant object searching
in scene illumination, translation, small rotation and occlusion changes
and then in the second stage, a machine learning method of support
vector machine (SVM) based on a feature of two dimensional (2D)
xy-color histogram is further utilized for pixel-wise disease
classification and quantification. The indoor experiment results
demonstrate the feasibility and potential of our proposed algorithm,
which could be implemented in real field situation for better
observation of plant disease development.
Abstract: In this paper, center conditions and bifurcation of limit cycles at the nilpotent critical point in a class of quintic polynomial differential system are investigated.With the help of computer algebra system MATHEMATICA, the first 10 quasi Lyapunov constants are deduced. As a result, sufficient and necessary conditions in order to have a center are obtained. The fact that there exist 10 small amplitude limit cycles created from the three order nilpotent critical point is also proved. Henceforth we give a lower bound of cyclicity of three-order nilpotent critical point for quintic Lyapunov systems. At last, we give an system which could bifurcate 10 limit circles.
Abstract: Tasks of an application program of an embedded system are managed by the scheduler of a real-time operating system
(RTOS). Most RTOSs adopt just fixed priority scheduling, which is not optimal in all cases. Some applications require earliest deadline
first (EDF) scheduling, which is an optimal scheduling algorithm.
In order to develop an efficient real-time embedded system, the
scheduling algorithm of the RTOS should be selectable. The paper presents a method to customize the scheduler using aspectoriented
programming. We define aspects to replace the fixed priority scheduling mechanism of an OSEK OS with an EDF scheduling
mechanism. By using the aspects, we can customize the scheduler
without modifying the original source code. We have applied the
aspects to an OSEK OS and get a customized operating system with
EDF scheduling. The evaluation results show that the overhead of
aspect-oriented programming is small enough.
Abstract: This paper will first describe predictor controllers
when the proportional-integral-derivative (PID) controllers are
inactive for procedures that have large delay time (LDT) in transfer
stage. Therefore in those states, the predictor controllers are better
than the PID controllers, then compares three types of predictor
controllers. The value of these controller-s parameters are obtained
by trial and error method, so here an effort has been made to obtain
these parameters by Ziegler-Nichols method. Eventually in this paper
Ziegler-Nichols method has been described and finally, a PIP
controller has been designed for a thermal system, which circulates
hot air to keep the temperature of a chamber constant.
Abstract: This study aims to segment objects using the K-means
algorithm for texture features. Firstly, the algorithm transforms color
images into gray images. This paper describes a novel technique for
the extraction of texture features in an image. Then, in a group of
similar features, objects and backgrounds are differentiated by using
the K-means algorithm. Finally, this paper proposes a new object
segmentation algorithm using the morphological technique. The
experiments described include the segmentation of single and multiple
objects featured in this paper. The region of an object can be
accurately segmented out. The results can help to perform image
retrieval and analyze features of an object, as are shown in this paper.
Abstract: In this paper, a novel scheme is proposed for ownership identification and authentication using color images by deploying Cryptography and Digital Watermarking as underlaying technologies. The former is used to compute the contents based hash and the latter to embed the watermark. The host image that will claim to be the rightful owner is first transformed from RGB to YST color space exclusively designed for watermarking based applications. Geometrically YS ÔèÑ T and T channel corresponds to the chrominance component of color image, therefore suitable for embedding the watermark. The T channel is divided into 4×4 nonoverlapping blocks. The size of block is important for enhanced localization, security and low computation. Each block along with ownership information is then deployed by SHA160, a one way hash function to compute the content based hash, which is always unique and resistant against birthday attack instead of using MD5 that may raise the condition i.e. H(m)=H(m'). The watermark payload varies from block to block and computed by the variance factorα . The quality of watermarked images is quite high both subjectively and objectively. Our scheme is blind, computationally fast and exactly locates the tampered region.
Abstract: Ranked set sampling (RSS) was first suggested to increase the efficiency of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this method. When a concomitant variable is available, ratio estimation based on ranked set sampling was proposed. This ratio estimator is more efficient than that based on SRS. In this paper some ratio type estimators of the population mean based on RSS are suggested. These estimators are found to be more efficient than the estimators of similar form using simple random sample.
Abstract: Power consumption of nodes in ad hoc networks is a
critical issue as they predominantly operate on batteries. In order to
improve the lifetime of an ad hoc network, all the nodes must be
utilized evenly and the power required for connections must be
minimized. In this project a link layer algorithm known as Power
Aware medium Access Control (PAMAC) protocol is proposed
which enables the network layer to select a route with minimum total
power requirement among the possible routes between a source and a
destination provided all nodes in the routes have battery capacity
above a threshold. When the battery capacity goes below a
predefined threshold, routes going through these nodes will be
avoided and these nodes will act only as source and destination.
Further, the first few nodes whose battery power drained to the set
threshold value are pushed to the exterior part of the network and the
nodes in the exterior are brought to the interior. Since less total
power is required to forward packets for each connection. The
network layer protocol AOMDV is basically an extension to the
AODV routing protocol. AOMDV is designed to form multiple
routes to the destination and it also avoid the loop formation so that it
reduces the unnecessary congestion to the channel. In this project, the
performance of AOMDV is evaluated using PAMAC as a MAC layer
protocol and the average power consumption, throughput and
average end to end delay of the network are calculated and the results
are compared with that of the other network layer protocol AODV.
Abstract: The compression-absorption heat pump (C-A HP), one
of the promising heat recovery equipments that make process hot
water using low temperature heat of wastewater, was evaluated by
computer simulation. A simulation program was developed based on
the continuity and the first and second laws of thermodynamics. Both
the absorber and desorber were modeled using UA-LMTD method. In
order to prevent an unfeasible temperature profile and to reduce
calculation errors from the curved temperature profile of a mixture,
heat loads were divided into lots of segments. A single-stage
compressor was considered. A compressor cooling load was also
taken into account. An isentropic efficiency was computed from the
map data. Simulation conditions were given based on the system
consisting of ordinarily designed components. The simulation results
show that most of the total entropy generation occurs during the
compression and cooling process, thus suggesting the possibility that
system performance can be enhanced if a rectifier is introduced.
Abstract: Perceptions of quality from both designers and users
perspective have now stretched beyond the traditional usability,
incorporating abstract and subjective concepts. This has led to a shift
in human computer interaction research communities- focus; a shift
that focuses on achieving user experience (UX) by not only fulfilling
conventional usability needs but also those that go beyond them. The
term UX, although widely spread and given significant importance,
lacks consensus in its unified definition. In this paper, we survey
various UX definitions and modeling frameworks and examine them
as the foundation for proposing a UX evolution lifecycle framework
for understanding UX in detail. In the proposed framework we identify
the building blocks of UX and discuss how UX evolves in various
phases. The framework can be used as a tool to understand experience
requirements and evaluate them, resulting in better UX design and
hence improved user satisfaction.
Abstract: In this work, are discussed two formulations of the boundary element method - BEM to perform linear bending analysis of plates reinforced by beams. Both formulations are based on the Kirchhoff's hypothesis and they are obtained from the reciprocity theorem applied to zoned plates, where each sub-region defines a beam or a slab. In the first model the problem values are defined along the interfaces and the external boundary. Then, in order to reduce the number of degrees of freedom kinematics hypothesis are assumed along the beam cross section, leading to a second formulation where the collocation points are defined along the beam skeleton, instead of being placed on interfaces. On these formulations no approximation of the generalized forces along the interface is required. Moreover, compatibility and equilibrium conditions along the interface are automatically imposed by the integral equation. Thus, these formulations require less approximation and the total number of the degree s of freedom is reduced. In the numerical examples are discussed the differences between these two BEM formulations, comparing as well the results to a well-known finite element code.
Abstract: Microarray data profiles gene expression on a whole
genome scale, therefore, it provides a good way to study associations
between gene expression and occurrence or progression of cancer.
More and more researchers realized that microarray data is helpful
to predict cancer sample. However, the high dimension of gene
expressions is much larger than the sample size, which makes this
task very difficult. Therefore, how to identify the significant genes
causing cancer becomes emergency and also a hot and hard research
topic. Many feature selection algorithms have been proposed in
the past focusing on improving cancer predictive accuracy at the
expense of ignoring the correlations between the features. In this
work, a novel framework (named by SGS) is presented for stable gene
selection and efficient cancer prediction . The proposed framework
first performs clustering algorithm to find the gene groups where
genes in each group have higher correlation coefficient, and then
selects the significant genes in each group with Bayesian Lasso and
important gene groups with group Lasso, and finally builds prediction
model based on the shrinkage gene space with efficient classification
algorithm (such as, SVM, 1NN, Regression and etc.). Experiment
results on real world data show that the proposed framework often
outperforms the existing feature selection and prediction methods,
say SAM, IG and Lasso-type prediction model.