Abstract: The population structure of the Tor tambroides was
investigated with morphometric data (i.e. morphormetric
measurement and truss measurement). A morphometric analysis was
conducted to compare specimens from three waterfalls: Sunanta, Nan
Chong Fa and Wang Muang waterfalls at Khao Nan National Park,
Nakhon Si Thammarat, Southern Thailand. The results of stepwise
discriminant analysis on seven morphometric variables and 21 truss
variables per individual were the same as from a neural network. Fish
from three waterfalls were separated into three groups based on their
morphometric measurements. The morphometric data shows that the
nerual network model performed better than the stepwise
discriminant analysis.
Abstract: In this paper, we study the instability of the zero solution to a nonlinear differential equation with variable delay. By using the Lyapunov functional approach, some sufficient conditions for instability of the zero solution are obtained.
Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Abstract: Recently electric vehicles are becoming popular as an
alternative of conventional fossil fuel vehicles. Conventional Internal
Combustion Engine (ICE) vehicle uses fossil fuel which contributing
a major part of overall carbon emission in the environment. Carbon
and other green house gas emission are responsible for global
warming and resulting climate change. It becomes vital to evaluate
performance of vehicle based on emission. In this paper an effort has
been made to depict the picture of emission caused by vehicle and
scenario of Australia has taken into account. Effort has been made to
compare the fossil based vehicle with electric vehicle in phases. The
study also evaluates advancement in electric vehicle technology,
required infrastructure for sustainability and future scope of
developments. This paper also includes the evaluation of electric
vehicle concept for pollution control and sustainable transport
systems in future. This study can be a benchmark for development of
electric vehicle as low carbon emission alternative for the cities of
tomorrow.
Abstract: Rarefied gas flows are often occurred in micro electro
mechanical systems and classical CFD could not precisely anticipate
the flow and thermal behavior due to the high Knudsen number.
Therefore, the heat transfer and the fluid dynamics characteristics of
rarefied gas flows in both a two-dimensional simple microchannel
and geometry similar to single Knudsen compressor have been
investigated with a goal of increasing performance of a actual
Knudsen compressor by using a particle simulation method. Thermal
transpiration and thermal creep, which are rarefied gas dynamic
phenomena, that cause movement of the flow from less to higher
temperature is generated by using two different longitude temperature
gradients (Linear, Step) along the walls of the flow microchannel. In
this study the influence of amount of temperature gradient and
governing pressure in various Knudsen numbers and length-to-height
ratios have been examined.
Abstract: The right to housing is a basic need while good
quality and affordable housing is a reflection of a high quality of life.
However, housing remains a major problem for most, especially for
the bottom billions. Satisfaction on housing and neighbourhood
conditions are one of the important indicators that reflect quality of
life. These indicators are also important in the process of evaluating
housing policy with the objective to increase the quality of housing
and neighbourhood. The research method is purely based on a
quantitative method, using a survey. The findings show that housing
purchasing trend in urban Malaysia is determined by demographic
profiles, mainly by education level, age, gender and income. The
period of housing ownership also influenced the socio-cultural
interactions and satisfaction of house owners with their
neighbourhoods. The findings also show that the main concerns for
house buyers in urban areas are price and location of the house.
Respondents feel that houses in urban Malaysia is too expensive and
beyond their affordability. Location of houses and distance from
work place are also regarded as the main concern. However,
respondents are fairly satisfied with religious and socio-cultural
facilities in the housing areas and most importantly not many regard
ethnicity as an issue in their decision-making, when buying a house.
Abstract: The transient thermoelastic response of thick hollow cylinder made of functionally graded material under thermal loading is studied. The generalized coupled thermoelasticity based on the Green-Lindsay model is used. The thermal and mechanical properties of the functionally graded material are assumed to be varied in the radial direction according to a power law variation as a function of the volume fractions of the constituents. The thermal and elastic governing equations are solved by using Galerkin finite element method. All the finite element calculations were done by using commercial finite element program FlexPDE. The transient temperature, radial displacement, and thermal stresses distribution through the radial direction of the cylinder are plotted.
Abstract: Fluids are used for heat transfer in many engineering
equipments. Water, ethylene glycol and propylene glycol are some
of the common heat transfer fluids. Over the years, in an attempt to
reduce the size of the equipment and/or efficiency of the process,
various techniques have been employed to improve the heat transfer
rate of these fluids. Surface modification, use of inserts and
increased fluid velocity are some examples of heat transfer
enhancement techniques. Addition of milli or micro sized particles
to the heat transfer fluid is another way of improving heat transfer
rate. Though this looks simple, this method has practical problems
such as high pressure loss, clogging and erosion of the material of
construction. These problems can be overcome by using nanofluids,
which is a dispersion of nanosized particles in a base fluid.
Nanoparticles increase the thermal conductivity of the base fluid
manifold which in turn increases the heat transfer rate. In this work,
the heat transfer enhancement using aluminium oxide nanofluid has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach.
Abstract: Topical photodynamic therapy (PDT) with
5-aminolevulinic acid (ALA) is an alternative therapy for treating
superficial cancer, especially for skin or oral cancer. ALA, a precursor
of the photosensitizer protoporphyrin IX (PpIX), is present as
zwitterions and hydrophilic property which make the low permeability
through the cell membrane. Collagen is a traditional carrier; its
molecular composed various amino acids which bear positive charge
and negative charge. In order to utilize the ion-pairs with ALA and
collagen, the study employed various pH values adjusting the net
charge. The aim of this study was to compare a series collagen form,
including solution, gel and sponge to investigate the topical delivery
behavior of ALA. The in vivo confocal laser scanning microscopy
(CLSM) study demonstrated that PpIX generation ability was different
pattern after apply for 6 h. Gel type could generate high PpIX, and
archived more deep of skin depth.
Abstract: Methods to detect and localize time singularities of polynomial and quasi-polynomial ordinary differential equations are systematically presented and developed. They are applied to examples taken form different fields of applications and they are also compared to better known methods such as those based on the existence of linear first integrals or Lyapunov functions.
Abstract: Power flow (PF) study, which is performed to
determine the power system static states (voltage magnitudes and
voltage angles) at each bus to find the steady state operating
condition of a system, is very important and is the most frequently
carried out study by power utilities for power system planning,
operation and control. In this paper, a counterpropagation neural
network (CPNN) is proposed to solve power flow problem under
different loading/contingency conditions for computing bus voltage
magnitudes and angles of the power system. The counterpropagation
network uses a different mapping strategy namely
counterpropagation and provides a practical approach for
implementing a pattern mapping task, since learning is fast in this
network. The composition of the input variables for the proposed
neural network has been selected to emulate the solution process of a
conventional power flow program. The effectiveness of the proposed
CPNN based approach for solving power flow is demonstrated by
computation of bus voltage magnitudes and voltage angles for
different loading conditions and single line-outage contingencies in
IEEE 14-bus system.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: The model-based approach to user interface design
relies on developing separate models capturing various aspects about
users, tasks, application domain, presentation and dialog structures.
This paper presents a task modeling approach for user interface
design and aims at exploring mappings between task, domain and
presentation models. The basic idea of our approach is to identify
typical configurations in task and domain models and to investigate
how they relate each other. A special emphasis is put on applicationspecific
functions and mappings between domain objects and
operational task structures. In this respect, we will address two
layers in task decomposition: a functional (planning) layer and an
operational layer.
Abstract: In the urban traffic network, the intersections are the
“bottleneck point" of road network capacity. And the arterials are the
main body in road network and the key factor which guarantees the
normal operation of the city-s social and economic activities. The
rapid increase in vehicles leads to seriously traffic jam and cause the
increment of vehicles- delay. Most cities of our country are
traditional single control system, which cannot meet the need for the
city traffic any longer. In this paper, Synchro6.0 as a platform to
minimize the intersection delay, optimizesingle signal cycle and split
for Zhonghua Street in Handan City. Meanwhile, linear control
system uses to optimize the phase for the t arterial road in this
system. Comparing before and after use the control, capacities and
service levels of this road and the adjacent road have improved
significantly.
Abstract: The mineral having chemical compositional formula MgAl2O4 is called “spinel". The ferrites crystallize in spinel structure are known as spinel-ferrites or ferro-spinels. The spinel structure has a fcc cage of oxygen ions and the metallic cations are distributed among tetrahedral (A) and octahedral (B) interstitial voids (sites). The X-ray diffraction (XRD) intensity of each Bragg plane is sensitive to the distribution of cations in the interstitial voids of the spinel lattice. This leads to the method of determination of distribution of cations in the spinel oxides through XRD intensity analysis. The computer program for XRD intensity analysis has been developed in C language and also tested for the real experimental situation by synthesizing the spinel ferrite materials Mg0.6Zn0.4AlxFe2- xO4 and characterized them by X-ray diffractometry. The compositions of Mg0.6Zn0.4AlxFe2-xO4(x = 0.0 to 0.6) ferrites have been prepared by ceramic method and powder X-ray diffraction patterns were recorded. Thus, the authenticity of the program is checked by comparing the theoretically calculated data using computer simulation with the experimental ones. Further, the deduced cation distributions were used to fit the magnetization data using Localized canting of spins approach to explain the “recovery" of collinear spin structure due to Al3+ - substitution in Mg-Zn ferrites which is the case if A-site magnetic dilution and non-collinear spin structure. Since the distribution of cations in the spinel ferrites plays a very important role with regard to their electrical and magnetic properties, it is essential to determine the cation distribution in spinel lattice.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.
Abstract: Long Term Evolution (LTE) is a 4G wireless
broadband technology developed by the Third Generation
Partnership Project (3GPP) release 8, and it's represent the
competitiveness of Universal Mobile Telecommunications System
(UMTS) for the next 10 years and beyond. The concepts for LTE
systems have been introduced in 3GPP release 8, with objective of
high-data-rate, low-latency and packet-optimized radio access
technology. In this paper, performance of different TCP variants
during LTE network investigated. The performance of TCP over
LTE is affected mostly by the links of the wired network and total
bandwidth available at the serving base station. This paper describes
an NS-2 based simulation analysis of TCP-Vegas, TCP-Tahoe, TCPReno,
TCP-Newreno, TCP-SACK, and TCP-FACK, with full
modeling of all traffics of LTE system. The Evaluation of the
network performance with all TCP variants is mainly based on
throughput, average delay and lost packet. The analysis of TCP
performance over LTE ensures that all TCP's have a similar
throughput and the best performance return to TCP-Vegas than other
variants.
Abstract: Banishing hunger from the face of earth has been
frequently expressed in various international, national and regional
level conferences since 1974. Providing food security has become
important issue across the world particularly in developing countries.
In a developing country like India, where growth rate of population is
more than that of the food grains production, food security is a
question of great concern. According to the International Food Policy
Research Institute's Global Hunger Index, 2011, India ranks 67 of the
81 countries of the world with the worst food security status. After
Green Revolution, India became a food surplus country. Its
production has increased from 74.23 million tonnes in 1966-67 to
257.44 million tonnes in 2011-12. But after achieving selfsufficiency
in food during last three decades, the country is now
facing new challenges due to increasing population, climate change,
stagnation in farm productivity. Therefore, the main objective of the
present paper is to examine the food security situation at national
level in the country and further to explain the paradox of food
insecurity in a food surplus state of India i.e in Punjab at micro level.
In order to achieve the said objectives, secondary data collected from
the Ministry of Agriculture and the Agriculture department of Punjab
State was analyzed. The result of the study showed that despite
having surplus food production the country is still facing food
insecurity problem at micro level. Within the Kandi belt of Punjab
state, the area adjacent to plains is food secure while the area along
the hills falls in food insecure zone.
The present paper is divided into following three sections (i)
Introduction, (ii) Analysis of food security situation at national level
as well as micro level (Kandi belt of Punjab State) (iii) Concluding
Observations