Abstract: Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.
Abstract: This paper discusses the Chinese Language Teaching as a Second Language by focusing on Immersion Teaching. Researchers used narrative literature review to describe the current states of both art and science in focused areas of inquiry. Immersion teaching comes with a standard that teachers must reliably meet. Chinese language-immersion instruction consists of language and content lessons, including functional usage of the language, academic language, authentic language, and correct Chinese sociocultural language. Researchers used narrative literature reviews to build a scientific knowledge base. Researchers collected all the important points of discussion, and put them here with reference to the specific field where this paper is originally based on. The findings show that Chinese Language in immersion teaching is not like standard foreign language classroom; immersion setting provides more opportunities to teach students colloquial language than academic. Immersion techniques also introduce a language’s cultural and social contexts in a meaningful and memorable way. It is particularly important that immersion teachers connect classwork with real-life experiences. Immersion also includes more elements of discovery and inquiry based learning than do other kinds of instructional practices. Students are always and consistently interpreted the conclusions and context clues.
Abstract: This paper presents an analytical study on the
behavior of reinforced concrete walls with rectangular cross section.
Several experiments on such walls have been selected to be studied.
Database from various experiments were collected and nominal shear
wall strengths have been calculated using formulas, such as those of
the ACI (American), NZS (New Zealand), Mexican (NTCC), and
Wood and Barda equations. Subsequently, nominal shear wall
strengths from the formulas were compared with the ultimate shear
wall strengths from the database. These formulas vary substantially in
functional form and do not account for all variables that affect the
response of walls. There is substantial scatter in the predicted values
of ultimate shear strength. Two new semi empirical equations are
developed using data from tests of 57 walls for transitions walls and
27 for slender walls with the objective of improving the prediction of
peak strength of walls with the most possible accurate.
Abstract: Solar water heating is a thermodynamic process of
heating water using sunlight with the help of solar water heater. Thus,
solar water heater is a device used to harness solar energy. In this
paper, a modified solar water heating system (MSWHS) has been
proposed over flat plate collector (FPC) and Evacuated tube collector
(ETC). The modifications include selection of materials other than
glass, and glass wool which are conventionally used for fabricating
FPC and ETC. Some modifications in design have also been
proposed. Its collector is made of double layer of semi-cylindrical
acrylic tubes and fibre reinforced plastic (FRP) insulation base. Water
tank is made of double layer of acrylic sheet except base and north
wall. FRP is used in base and north wall of the water tank. A concept
of equivalent thickness has been utilised for calculating the
dimensions of collector plate, acrylic tube and tank. A thermal model for the proposed design of MSWHS is developed
and simulation is carried out on MATLAB for the capacity of 200L
MSWHS having collector area of 1.6 m2, length of acrylic tubes of
2m at an inclination angle 25° which is taken nearly equal to the
latitude of the given location. Latitude of Allahabad is 24.45° N. The
results show that the maximum temperature of water in tank and tube
has been found to be 71.2°C and 73.3°C at 17:00hr and 16:00hr
respectively in March for the climatic data of Allahabad. Theoretical performance analysis has been carried out by varying
number of tubes of collector, the tank capacity and climatic data for
given months of winter and summer.
Abstract: The Petri nets are the first standard for business
process modeling. Most probably, it is one of the core reasons why
all new standards created afterwards have to be so reformed as to
reach the stage of mapping the new standard onto Petri nets. The paper presents a business process repository based on a
universal database. The repository provides the possibility the data
about a given process to be stored in three different ways. Business
process repository is developed with regard to the reformation of a
given model to a Petri net in order to be easily simulated. Two different techniques for business process simulation based on
Petri nets - Yasper and Woflan are discussed. Their advantages and
drawbacks are outlined. The way of simulating business process
models, stored in the Business process repository is shown.
Abstract: In this paper, a novel fuzzy approach is developed
while solving the Dynamic Routing and Wavelength Assignment
(DRWA) problem in optical networks with Wavelength Division
Multiplexing (WDM). In this work, the effect of nonlinear and linear
impairments such as Four Wave Mixing (FWM) and amplifier
spontaneous emission (ASE) noise are incorporated respectively. The
novel algorithm incorporates fuzzy logic controller (FLC) to reduce
the effect of FWM noise and ASE noise on a requested lightpath
referred in this work as FWM aware fuzzy dynamic routing and
wavelength assignment algorithm. The FWM crosstalk products and
the static FWM noise power per link are pre computed in order to
reduce the set up time of a requested lightpath, and stored in an
offline database. These are retrieved during the setting up of a
lightpath and evaluated online taking the dynamic parameters like
cost of the links into consideration.
Abstract: Food supply chain is one of the most complex supply
chain networks due to its perishable nature and customer oriented
products, and food safety is the major concern for this industry. IT
system could help to minimize the production and consumption of
unsafe food by controlling and monitoring the entire system.
However, there have been many issues in adoption of IT system in
this industry specifically within SMEs sector. With this regard, this
study presents a novel approach to use IT and tractability systems in
the food supply chain, using application of RFID and central
database.
Abstract: Computer aided diagnosis systems provide vital
opinion to radiologists in the detection of early signs of breast cancer
from mammogram images. Architectural distortions, masses and
microcalcifications are the major abnormalities. In this paper, a
computer aided diagnosis system has been proposed for
distinguishing abnormal mammograms with architectural distortion
from normal mammogram. Four types of texture features GLCM
texture, GLRLM texture, fractal texture and spectral texture features
for the regions of suspicion are extracted. Support vector machine
has been used as classifier in this study. The proposed system yielded
an overall sensitivity of 96.47% and an accuracy of 96% for
mammogram images collected from digital database for screening
mammography database.
Abstract: In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
Abstract: One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
Abstract: Sustainability is a very important and heavily
discussed subject, expanding through tourism as well. The study
proposition was to collect data and present it to the competent bodies
so they can mold their public policies to improve the conditions of
the site. It was hypothesized that the lack of data is currently
affecting the quality of life and the sustainable development of the
site and the tourism. The research was held in Mateiros, a city in the
state of Tocantins (TO)/Brasil near Palmas, its capital city. Because
of the concentration of tourists during the high season and several
tourist attractions being around, the research took place in Mateiros.
The methodological procedure had a script of theoretical construction
and investigation of the deductive scientific method parameters
through a case study in the Jalapão/TO/Brazil region, using it as a
tool for a questionnaire given to the competent bodies in an interview
system with the UN sustainability indexes as a base. In the three
sustainable development scope: environmental, social and economic,
the results indicated that the data presented by the interviewed were
scarce or nonexistent. It shows that more research is necessary,
providing the tools for the ones responsible to propose action plans to
improve the site, strengthening the tourism and making it even more
sustainable.
Abstract: A knowledge base stores facts and rules about the
world that applications can use for the purpose of reasoning. By
applying the concept of granular computing to a knowledge base,
several advantages emerge. These can be harnessed by applications
to improve their capabilities and performance. In this paper, the
concept behind such a construct, called a granular knowledge cube,
is defined, and its intended use as an instrument that manages to
cope with different data types and detect knowledge domains is
elaborated. Furthermore, the underlying architecture, consisting of the
three layers of the storing, representing, and structuring of knowledge,
is described. Finally, benefits as well as challenges of deploying it
are listed alongside application types that could profit from having
such an enhanced knowledge base.
Abstract: To construct the lumped spring-mass model
considering the occupants for the offset frontal crash, the SISAME
software and the NHTSA test data were used. The data on 56 kph 40%
offset frontal vehicle to deformable barrier crash test of a MY2007
Mazda 6 4-door sedan were obtained from NHTSA test database. The
overall behaviors of B-pillar and engine of simulation models agreed
very well with the test data. The trends of accelerations at the driver
and passenger head were similar but big differences in peak values.
The differences of peak values caused the large errors of the HIC36
and 3 ms chest g’s. To predict well the behaviors of dummies, the
spring-mass model for the offset frontal crash needs to be improved.
Abstract: In this paper, we are interested in the problem of
finding similar images in a large database. For this purpose we
propose a new algorithm based on a combination of the 2-D
histogram intersection in the HSV space and statistical moments. The
proposed histogram is based on a 3x3 window and not only on the
intensity of the pixel. This approach overcome the drawback of the
conventional 1-D histogram which is ignoring the spatial distribution
of pixels in the image, while the statistical moments are used to
escape the effects of the discretisation of the color space which is
intrinsic to the use of histograms. We compare the performance of
our new algorithm to various methods of the state of the art and we
show that it has several advantages. It is fast, consumes little memory
and requires no learning. To validate our results, we apply this
algorithm to search for similar images in different image databases.
Abstract: Thousands of organisations store important and
confidential information related to them, their customers, and their
business partners in databases all across the world. The stored data
ranges from less sensitive (e.g. first name, last name, date of birth) to
more sensitive data (e.g. password, pin code, and credit card
information). Losing data, disclosing confidential information or
even changing the value of data are the severe damages that
Structured Query Language injection (SQLi) attack can cause on a
given database. It is a code injection technique where malicious SQL
statements are inserted into a given SQL database by simply using a
web browser. In this paper, we propose an effective pattern
recognition neural network model for detection and classification of
SQLi attacks. The proposed model is built from three main elements
of: a Uniform Resource Locator (URL) generator in order to generate
thousands of malicious and benign URLs, a URL classifier in order
to: 1) classify each generated URL to either a benign URL or a
malicious URL and 2) classify the malicious URLs into different
SQLi attack categories, and a NN model in order to: 1) detect either a
given URL is a malicious URL or a benign URL and 2) identify the
type of SQLi attack for each malicious URL. The model is first
trained and then evaluated by employing thousands of benign and
malicious URLs. The results of the experiments are presented in
order to demonstrate the effectiveness of the proposed approach.
Abstract: This paper addresses the issue of the autonomous
mobile robot (AMR) navigation task based on the hybrid control
modes. The novel hybrid control mode, based on multi-sensors
information by using the fuzzy approach, has been presented in this
research. The system operates in real time, is robust, enables the robot
to operate with imprecise knowledge, and takes into account the
physical limitations of the environment in which the robot moves,
obtaining satisfactory responses for a large number of different
situations. An experiment is simulated and carried out with a pioneer
mobile robot. From the experimental results, the effectiveness and
usefulness of the proposed AMR obstacle avoidance and navigation
scheme are confirmed. The experimental results show the feasibility,
and the control system has improved the navigation accuracy. The
implementation of the controller is robust, has a low execution time,
and allows an easy design and tuning of the fuzzy knowledge base.
Abstract: The composite pavement system considered in this
paper is composed of a functional surface layer, a fiber reinforced
asphalt middle layer and a fiber reinforced lean concrete base layer.
The mix design of the fiber reinforced lean concrete corresponds to the
mix composition of conventional lean concrete but reinforced by
fibers. The quasi-absence of research on the durability or long-term
performances (fatigue, creep, etc.) of such mix design stresses the
necessity to evaluate experimentally the long-term characteristics of
this layer composition. This study tests the creep characteristics as one
of the long-term characteristics of the fiber reinforced lean concrete
layer for composite pavement using a new creep device. The test
results reveal that the lean concrete mixed with fiber reinforcement
and fly ash develops smaller creep than the conventional lean
concrete. The results of the application of the CEB-FIP prediction
equation indicate that a modified creep prediction equation should be
developed to fit with the new mix design of the layer.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
Abstract: Speech Segmentation is the measure of the change
point detection for partitioning an input speech signal into regions
each of which accords to only one speaker. In this paper, we apply
two features based on multi-scale product (MP) of the clean speech,
namely the spectral centroid of MP, and the zero crossings rate of
MP. We focus on multi-scale product analysis as an important tool
for segmentation extraction. The MP is based on making the product
of the speech wavelet transform coefficients (WTC). We have
estimated our method on the Keele database. The results show the
effectiveness of our method. It indicates that the two features can find
word boundaries, and extracted the segments of the clean speech.
Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.