Abstract: Using Internet communication, new home electronics
have functions of monitoring and control from remote. However in
many case these electronics work as standalone, and old electronics
are not followed. Then, we developed the total remote system include
not only new electronics but olds. This systems node is a adapter of
electrical power plug that embed relay switch and some sensors, and
these nodes communicate with each other. the system server was build
on the Internet, and users access to this system from web browsers.
To reduce the cost to set up of this system, communication between
adapters are used ZigBee wireless network instead of wired LAN
cable[3]. From measured RSSI(received signal strength indicator)
information between each nodes, the system can estimate roughly
adapters were mounted on which room, and where in the room. So
also it reduces the cost of mapping nodes. Using this system, energy
saving and house monitoring are expected.
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
Abstract: This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.
Abstract: The classical temporal scan statistic is often used to
identify disease clusters. In recent years, this method has become as a
very popular technique and its field of application has been notably
increased. Many bioinformatic problems have been solved with this
technique. In this paper a new scan fuzzy method is proposed. The
behaviors of classic and fuzzy scan techniques are studied with
simulated data. ROC curves are calculated, being demonstrated the
superiority of the fuzzy scan technique.
Abstract: This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.
Abstract: InGaAsN and GaAsN epitaxial layers with similar
nitrogen compositions in a sample were successfully grown on a
GaAs (001) substrate by solid source molecular beam epitaxy. An
electron cyclotron resonance nitrogen plasma source has been used to
generate atomic nitrogen during the growth of the nitride layers. The
indium composition changed from sample to sample to give
compressive and tensile strained InGaAsN layers. Layer
characteristics have been assessed by high-resolution x-ray
diffraction to determine the relationship between the lattice constant
of the GaAs1-yNy layer and the fraction x of In. The objective was to
determine the In fraction x in an InxGa1-xAs1-yNy epitaxial layer which
exactly cancels the strain present in a GaAs1-yNy epitaxial layer with
the same nitrogen content when grown on a GaAs substrate.
Abstract: This essay presents applicative methods to reduce human exposure levels in the area around base transceiver stations in a environment with multiple sources based on ITU-T recommendation K.70. An example is presented to understand the mitigation techniques and their results and also to learn how they can be applied, especially in developing countries where there is not much research on non-ionizing radiations.
Abstract: Workflow Management Systems (WfMS) alloworganizations to streamline and automate business processes and reengineer their structure. One important requirement for this type of system is the management and computation of the Quality of Service(QoS) of processes and workflows. Currently, a range of Web processes and workflow languages exist. Each language can be characterized by the set of patterns they support. Developing andimplementing a suitable and generic algorithm to compute the QoSof processes that have been designed using different languages is a difficult task. This is because some patterns are specific to particular process languages and new patterns may be introduced in future versions of a language. In this paper, we describe an adaptive algorithm implemented to cope with these two problems. The algorithm is called adaptive since it can be dynamically changed as the patterns of a process language also change.
Abstract: Classification is an important topic in machine learning
and bioinformatics. Many datasets have been introduced for
classification tasks. A dataset contains multiple features, and the quality of features influences the classification accuracy of the dataset.
The power of classification for each feature differs. In this study, we
suggest the Classification Influence Index (CII) as an indicator of classification power for each feature. CII enables evaluation of the
features in a dataset and improved classification accuracy by transformation of the dataset. By conducting experiments using CII
and the k-nearest neighbor classifier to analyze real datasets, we confirmed that the proposed index provided meaningful improvement
of the classification accuracy.
Abstract: Malay Folk Literature in early childhood education
served as an important agent in child development that involved
emotional, thinking and language aspects. Up to this moment not
much research has been carried out in Malaysia particularly in the
teaching and learning aspects nor has there been an effort to publish
“big books." Hence this article will discuss the stance taken by
university undergraduate students, teachers and parents in evaluating
Malay Folk Literature in early childhood education to be used as big
books. The data collated and analyzed were taken from 646
respondents comprising 347 undergraduates and 299 teachers. Results
of the study indicated that Malay Folk Literature can be absorbed into
teaching and learning for early childhood with a mean of 4.25 while it
can be in big books with a mean of 4.14. Meanwhile the highest mean
value required for placing Malay Folk Literature genre as big books in
early childhood education rests on exemplary stories for
undergraduates with mean of 4.47; animal fables for teachers with a
mean of 4.38. The lowest mean value of 3.57 is given to lipurlara
stories. The most popular Malay Folk Literature found suitable for
early children is Sang Kancil and the Crocodile, followed by Bawang
Putih Bawang Merah. Pak Padir, Legends of Mahsuri, Origin of
Malacca, and Origin of Rainbow are among the popular stories as
well. Overall the undergraduates show a positive attitude toward all
the items compared to teachers. The t-test analysis has revealed a non
significant relationship between the undergraduate students and
teachers with all the items for the teaching and learning of Malay Folk
Literature.
Abstract: A novel idea presented in this paper is to combine
multihop routing with single-frequency networks (SFNs) for a
broadcasting scenario. An SFN is a set of multiple nodes that transmit
the same data simultaneously, resulting in transmitter macrodiversity.
Two of the most important performance factors of multihop
networks, node reachability and routing robustness, are analyzed.
Simulation results show that our proposed SFN-D routing algorithm
improves the node reachability by 37 percentage points as compared
to non-SFN multihop routing. It shows a diversity gain of 3.7 dB,
meaning that 3.7 dB lower transmission powers are required for the
same reachability. Even better results are possible for larger
networks. If an important node becomes inactive, this algorithm can
find new routes that a non-SFN scheme would not be able to find.
Thus, two of the major problems in multihopping are addressed;
achieving robust routing as well as improving node reachability or
reducing transmission power.
Abstract: A dissimilarity measure between the empiric
characteristic functions of the subsamples associated to the different
classes in a multivariate data set is proposed. This measure can be
efficiently computed, and it depends on all the cases of each class. It
may be used to find groups of similar classes, which could be joined
for further analysis, or it could be employed to perform an
agglomerative hierarchical cluster analysis of the set of classes. The
final tree can serve to build a family of binary classification models,
offering an alternative approach to the multi-class SVM problem. We
have tested this dendrogram based SVM approach with the oneagainst-
one SVM approach over four publicly available data sets,
three of them being microarray data. Both performances have been
found equivalent, but the first solution requires a smaller number of
binary SVM models.
Abstract: In this paper, we propose a dynamic TDMA slot
reservation (DTSR) protocol for cognitive radio ad hoc networks.
Quality of Service (QoS) guarantee plays a critically important role
in such networks. We consider the problem of providing QoS
guarantee to users as well as to maintain the most efficient use of
scarce bandwidth resources. According to one hop neighboring
information and the bandwidth requirement, our proposed protocol
dynamically changes the frame length and the transmission schedule.
A dynamic frame length expansion and shrinking scheme that
controls the excessive increase of unassigned slots has been
proposed. This method efficiently utilizes the channel bandwidth by
assigning unused slots to new neighboring nodes and increasing the
frame length when the number of slots in the frame is insufficient to
support the neighboring nodes. It also shrinks the frame length when
half of the slots in the frame of a node are empty. An efficient slot
reservation protocol not only guarantees successful data
transmissions without collisions but also enhance channel spatial
reuse to maximize the system throughput. Our proposed scheme,
which provides both QoS guarantee and efficient resource utilization,
be employed to optimize the channel spatial reuse and maximize the
system throughput. Extensive simulation results show that the
proposed mechanism achieves desirable performance in multichannel
multi-rate cognitive radio ad hoc networks.
Abstract: This paper compares six approaches of object serialization
from qualitative and quantitative aspects. Those are object
serialization in Java, IDL, XStream, Protocol Buffers, Apache Avro,
and MessagePack. Using each approach, a common example is
serialized to a file and the size of the file is measured. The qualitative
comparison works are investigated in the way of checking whether
schema definition is required or not, whether schema compiler is
required or not, whether serialization is based on ascii or binary, and
which programming languages are supported. It is clear that there
is no best solution. Each solution makes good in the context it was
developed.
Abstract: The paper discusses optimising work on a method of processing ceramic / metal composite coatings for various applications and is based on preliminary work on processing anodes for solid oxide fuel cells (SOFCs). The composite coating is manufactured by the electroless co-deposition of nickel and yttria stabilised zirconia (YSZ) simultaneously on to a ceramic substrate. The effect on coating characteristics of substrate surface treatments and electroless nickel bath parameters such as pH and agitation methods are also investigated. Characterisation of the resulting deposit by scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDXA) is also discussed.
Abstract: This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in the design phase was to enhance the damping capability minimizing the loss in static stiffness through implementation of composite material interfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machining system, as well as the surface roughness of the machined workpieces. The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take into consideration the interaction between the elastic structure of the machine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.
Abstract: In the Equivalent Transformation (ET) computation
model, a program is constructed by the successive accumulation of
ET rules. A method by meta-computation by which a correct ET
rule is generated has been proposed. Although the method covers a
broad range in the generation of ET rules, all important ET rules
are not necessarily generated. Generation of more ET rules can be
achieved by supplementing generation methods which are specialized
for important ET rules. A Specialization-by-Equation (Speq) rule is
one of those important rules. A Speq rule describes a procedure in
which two variables included in an atom conjunction are equalized
due to predicate constraints. In this paper, we propose an algorithm
that systematically and recursively generate Speq rules and discuss
its effectiveness in the synthesis of ET programs. A Speq rule is
generated based on proof of a logical formula consisting of given
atom set and dis-equality. The proof is carried out by utilizing some
ET rules and the ultimately obtained rules in generating Speq rules.
Abstract: The purpose of this study is to investiagte the use of
the ecommerce website in Indonesia as a developing country. The
ecommerce website has been identified having the significant impact
on business activities in particular solving the geographical problem
for islanded countries likes Indonesia. Again, website is identified as
a crucial marketing tool. This study presents the effect of quality and
features on the use and user satisfaction employing ecommerce
websites. Survey method for 115 undergraduate students of
Management Department in Andalas University who are attending
Management Information Systems (SIM) class have been
undertaken. The data obtained is analyzed using Structural Equation
Modeling (SEM) using SmartPLS program. This result found that
quality of system and information, feature as well satisfaction
influencing the use ecommerce website in Indonesia contexts.
Abstract: The link between Gröbner basis and linear algebra was
described by Lazard [4,5] where he realized the Gr¨obner basis
computation could be archived by applying Gaussian elimination over
Macaulay-s matrix .
In this paper, we indicate how same technique may be used to
SAGBI- Gröbner basis computations in invariant rings.
Abstract: Naïve Bayes classifiers are simple probabilistic
classifiers. Classification extracts patterns by using data file with a set
of labeled training examples and is currently one of the most
significant areas in data mining. However, Naïve Bayes assumes the
independence among the features. Structural learning among the
features thus helps in the classification problem. In this study, the use
of structural learning in Bayesian Network is proposed to be applied
where there are relationships between the features when using the
Naïve Bayes. The improvement in the classification using structural
learning is shown if there exist relationship between the features or
when they are not independent.