Abstract: Droplet size distributions in the cold spray of a fuel
are important in observed combustion behavior. Specification of
droplet size and velocity distributions in the immediate downstream
of injectors is also essential as boundary conditions for advanced
computational fluid dynamics (CFD) and two-phase spray transport
calculations. This paper describes the development of a new model to
be incorporated into maximum entropy principle (MEP) formalism
for prediction of droplet size distribution in droplet formation region.
The MEP approach can predict the most likely droplet size and
velocity distributions under a set of constraints expressing the
available information related to the distribution.
In this article, by considering the mechanisms of turbulence
generation inside the nozzle and wave growth on jet surface, it is
attempted to provide a logical framework coupling the flow inside the
nozzle to the resulting atomization process. The purpose of this paper
is to describe the formulation of this new model and to incorporate it
into the maximum entropy principle (MEP) by coupling sub-models
together using source terms of momentum and energy. Comparison
between the model prediction and experimental data for a gas turbine
swirling nozzle and an annular spray indicate good agreement
between model and experiment.
Abstract: We report in this paper the model adopted by our
system of continuous speech recognition in Arab language SySRA
and the results obtained until now. This system uses the database
Arabdic-10 which is a corpus of word for the Arab language and
which was manually segmented. Phonetic decoding is represented
by an expert system where the knowledge base is translated in the
form of production rules. This expert system transforms a vocal
signal into a phonetic lattice. The higher level of the system takes
care of the recognition of the lattice thus obtained by deferring it in
the form of written sentences (orthographical Form). This level
contains initially the lexical analyzer which is not other than the
module of recognition. We subjected this analyzer to a set of
spectrograms obtained by dictating a score of sentences in Arab
language. The rate of recognition of these sentences is about 70%
which is, to our knowledge, the best result for the recognition of the
Arab language. The test set consists of twenty sentences from four
speakers not having taken part in the training.
Abstract: In this research, we study a control method of a multivehicle
system while considering the limitation of communication
range for each vehicles. When we control networked vehicles with
limitation of communication range, it is important to control the
communication network structure of a multi-vehicle system in order
to keep the network-s connectivity. From this, we especially aim to
control the network structure to the target structure. We formulate
the networked multi-vehicle system with some disturbance and the
communication constraints as a hybrid dynamical system, and then
we study the optimal control problems of the system. It is shown
that the system converge to the objective network structure in finite
time when the system is controlled by the receding horizon method.
Additionally, the optimal control probrems are convertible into the
mixed integer problems and these problems are solvable by some
branch and bound algorithm.
Abstract: The coastal sediments of West Port of Malaysia was monitored from Nov. 2009 to Oct. 2010 to assess spatial distribution of heavy metals As, Cu, Cd, Cr, Hg, Ni, Zn and Pb. Sediment samples were collected from 10 stations in dry and rainy season in West Port. The range concentrations measured (Mg/g dry weight ) were from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. The geochemical indexes used in this study were Geoaccumulation (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI); these indexes were used to evaluate the levels of sediment contaminations. The results of these indexes show that, the status of West Port sediment quality are moderately polluted by heavy metals except in arsenic which shows the high level of pollution.
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: Today, the working areas put forward the administration of change. In order to provide this; it is required from the organizations to be creative. Professional creativity in offices depends on an environment that enables the development of the organization only after the individual or collective exertions within the organization. By providing this environment, the organization will gain efficiency, productivity, and work pleasure. In order to bring up the workforce appropriate to the related expectations, the professional creativity of the office management and secretarial profession candidates should be evaluated, education programs appropriate to this and related directly with the service quality should be prepared and the future of this profession should be directed. The aim of this study is to ensure the attention to improve the prepared education program as well as the creative thoughts and their applications, when carrying out an office management and secretarial training. 144 students took place in this research and a questionnaire of 48 questions was carried out.
Abstract: Traditionally, VLSI implementations of spiking
neural nets have featured large neuron counts for fixed computations
or small exploratory, configurable nets. This paper presents the
system architecture of a large configurable neural net system
employing a dedicated mapping algorithm for projecting the targeted
biology-analog nets and dynamics onto the hardware with its
attendant constraints.
Abstract: Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.
Abstract: In order to increase in chickpea quality and
agroecosystem sustainability, field experiments were carried out in
2007 and 2008 growing seasons. In this research the effects of
different organic, chemical and biological fertilizers were
investigated on grain yield and quality of chickpea. Experimental
units were arranged in split-split plots based on randomized complete
blocks with three replications. The highest amounts of yield and yield
components were obtained in G1×N5 interaction. Significant
increasing of N, P, K, Fe and Mg content in leaves and grains
emphasized on superiority of mentioned treatment because each one
of these nutrients has an approved role in chlorophyll synthesis and
photosynthesis ability of the crop. The combined application of
compost, farmyard manure and chemical phosphorus (N5) had the
best grain quality due to high protein, starch and total sugar contents,
low crude fiber and reduced cooking time.
Abstract: The objectives were to identify cyanide-degrading
bacteria and study cyanide removal efficiency. Agrobacterium
tumefaciens SUTS 1 was isolated. This is a new strain of
microorganisms for cyanide degradation. The maximum growth rate
of SUTS 1 obtained 4.7 × 108 CFU/ml within 4 days. The cyanide
removal efficiency was studied at 25, 50, and 150 mg/L cyanide. The
residual cyanide, ammonia, nitrate, nitrite, pH, and cell counts were
analyzed. At 25 and 50 mg/L cyanide, SUTS 1 obtained similar
removal efficiency approximately 87.50%. At 150 mg/L cyanide,
SUTS 1 enhanced the cyanide removal efficiency up to 97.90%. Cell
counts of SUTS 1 increased when the cyanide concentration was set
at lower. The ammonia increased when the removal efficiency
increased. The nitrate increased when the ammonia decreased but the
nitrite did not detect in all experiments. pH values also increased
when the cyanide concentrations were set at higher.
Abstract: This paper presents an efficient emission constrained
economic dispatch algorithm that deals with nonlinear cost function
and constraints. It is then incorporated into the dynamic
programming based hydrothermal coordination program. The
program has been tested on a practical utility system having 32
thermal and 12 hydro generating units. Test results show that a slight
increase in production cost causes a substantial reduction in
emission.
Abstract: We introduce an algorithm based on the
morphological shared-weight neural network. Being nonlinear and
translation-invariant, the MSNN can be used to create better
generalization during face recognition. Feature extraction is
performed on grayscale images using hit-miss transforms that are
independent of gray-level shifts. The output is then learned by
interacting with the classification process. The feature extraction and
classification networks are trained together, allowing the MSNN to
simultaneously learn feature extraction and classification for a face.
For evaluation, we test for robustness under variations in gray levels
and noise while varying the network-s configuration to optimize
recognition efficiency and processing time. Results show that the
MSNN performs better for grayscale image pattern classification
than ordinary neural networks.
Abstract: Nowadays, the increase of human population every
year results in increasing of water usage and demand. Saen Saep
canal is important canal in Bangkok. The main objective of this study
is using Artificial Neural Network (ANN) model to estimate the
Chemical Oxygen Demand (COD) on data from 11 sampling sites.
The data is obtained from the Department of Drainage and Sewerage,
Bangkok Metropolitan Administration, during 2007-2011. The
twelve parameters of water quality are used as the input of the
models. These water quality indices affect the COD. The
experimental results indicate that the ANN model provides a high
correlation coefficient (R=0.89).
Abstract: We have developed a distributed asynchronous Web
based training system. In order to improve the scalability and robustness
of this system, all contents and functions are realized on mobile
agents. These agents are distributed to computers, and they can use
a Peer to Peer network that modified Content-Addressable Network.
In the proposed system, only text data can be included in a exercise.
To make our proposed system more useful, the mechanism that it not
only adapts to multimedia data but also it doesn-t influence the user-s
learning even if the size of exercise becomes large is necessary.
Abstract: This research aimed to find out the determining
factors for ISO 14001 EMS implementation among SMEs in
Malaysia from the Resource based view. A cross-sectional approach
using survey was conducted. A research model been proposed which
comprises of ISO 14001 EMS implementation as the criterion
variable while physical capital resources (i.e. environmental
performance tracking and organizational infrastructures), human
capital resources (i.e. top management commitment and support,
training and education, employee empowerment and teamwork) and
organizational capital resources (i.e. recognition and reward,
organizational culture and organizational communication) as the
explanatory variables. The research findings show that only
environmental performance tracking, top management commitment
and support and organizational culture are found to be positively and
significantly associated with ISO 14001 EMS implementation. It is
expected that this research will shed new knowledge and provide a
base for future studies about the role played by firm-s internal
resources.
Abstract: This study examined the effects of neuromuscular
training (NT) on limits of stability (LOS) in female individuals.
Twenty female basketball amateurs were assigned into NT
experimental group or control group by volunteer. All the players were
underwent regular basketball practice, 90 minutes, 3 times per week
for 6 weeks, but the NT experimental group underwent extra NT with
plyometric and core training, 50 minutes, 3 times per week for 6 weeks
during this period. Limits of stability (LOS) were evaluated by the
Biodex Balance System. One factor ANCOVA was used to examine
the differences between groups after training. The significant level for
statistic was set at p
Abstract: Education supported by mobile computers has been widely done for some time. Teachers have attempted to use mobile computers and to find concrete subjects for student-s fieldwork training in college education. The purpose of this research is to develop software for Personal Digital Assistant (PDA) to conduct fieldwork in our campus, and to report a fieldwork class using PDAs in the curriculum of the Department of Regional Environment Studies.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: In general, small-scale vegetables farmers experience
problems in improving the safety and quality of vegetables supplied
to high-class consumers in modern retailers. They also lack of
information to access market. The farmers group and/or cooperative
(FGC) should be able to assist its members by providing training in
handling and packing vegetables and enhancing marketing
capabilities to sell commodities to the modern retailers. This study
proposes an agri-food supply chain (ASC) model that involves the
corporate social responsibility (CSR) activities to cultivate the
capabilities of farmers to access market. Multi period ASC model is
formulated as Weighted Goal Programming (WGP) to analyze the
impacts of CSR programs to empower the FGCs in managing the
small-scale vegetables farmers. The results show that the proposed
model can be used to determine the priority of programs in order to
maximize the four goals to be achieved in the CSR programs.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.