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: Timetabling problems are often hard and timeconsuming
to solve. Most of the methods of solving them concern
only one problem instance or class. This paper describes a universal
method for solving large, highly constrained timetabling problems
from different domains. The solution is based on evolutionary
algorithm-s framework and operates on two levels – first-level
evolutionary algorithm tries to find a solution basing on given set of
operating parameters, second-level algorithm is used to establish
those parameters. Tabu search is employed to speed up the solution
finding process on first level. The method has been used to solve
three different timetabling problems with promising results.
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: Hepatitis C is an infectious disease transmitted by
blood and due to hepatitis C virus (HCV), which attacks the liver.
The infection is characterized by liver inflammation (hepatitis) that is
often asymptomatic but can progress to chronic hepatitis and later
cirrhosis and liver cancer. Our problem tends to highlight on the one
hand the prevalence of infectious disease in the population of the
region of Batna and on other hand the biological characteristics of
this disease by a screening and a specific diagnosis based on
serological tests, liver checkup (measurement of haematological and
biochemical parameters).
The results showed:
The serology of hepatitis C establishes the diagnosis of infection
with hepatitis C. In this study and with the serological test, 24 cases
of the disease of hepatitis C were found in 1000 suspected cases (7
cases with normal transaminases and 17 cases with elevated
transaminases). The prevalence of this disease in this study
population was 2.4%.
The presence of hepatitis C disrupts liver function including the
onset of cytolysis, cholestasis, jaundice, thrombocytopenia, and
coagulation disorders.
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: 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: In this paper we considered the Neumann problem for
the fourth order differential equation. First we define the weighted Sobolev space
2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution,
as well as give the description of the spectrum and of the domain of definition of the corresponding operator.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
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
Abstract: Gene expression profiling is rapidly evolving into a
powerful technique for investigating tumor malignancies. The
researchers are overwhelmed with the microarray-based platforms
and methods that confer them the freedom to conduct large-scale
gene expression profiling measurements. Simultaneously,
investigations into cross-platform integration methods have started
gaining momentum due to their underlying potential to help
comprehend a myriad of broad biological issues in tumor diagnosis,
prognosis, and therapy. However, comparing results from different
platforms remains to be a challenging task as various inherent
technical differences exist between the microarray platforms. In this
paper, we explain a simple ratio-transformation method, which can
provide some common ground for cDNA and Affymetrix platform
towards cross-platform integration. The method is based on the
characteristic data attributes of Affymetrix- and cDNA- platform. In
the work, we considered seven childhood leukemia patients and their
gene expression levels in either platform. With a dataset of 822
differentially expressed genes from both these platforms, we carried
out a specific ratio-treatment to Affymetrix data, which subsequently
showed an improvement in the relationship with the cDNA data.
Abstract: In this paper a modification on Levenberg-Marquardt algorithm for MLP neural network learning is proposed. The proposed algorithm has good convergence. This method reduces the amount of oscillation in learning procedure. An example is given to show usefulness of this method. Finally a simulation verifies the results of proposed method.
Abstract: Term Extraction, a key data preparation step in Text
Mining, extracts the terms, i.e. relevant collocation of words,
attached to specific concepts (e.g. genetic-algorithms and decisiontrees
are terms associated to the concept “Machine Learning" ). In
this paper, the task of extracting interesting collocations is achieved
through a supervised learning algorithm, exploiting a few
collocations manually labelled as interesting/not interesting. From
these examples, the ROGER algorithm learns a numerical function,
inducing some ranking on the collocations. This ranking is optimized
using genetic algorithms, maximizing the trade-off between the false
positive and true positive rates (Area Under the ROC curve). This
approach uses a particular representation for the word collocations,
namely the vector of values corresponding to the standard statistical
interestingness measures attached to this collocation. As this
representation is general (over corpora and natural languages),
generality tests were performed by experimenting the ranking
function learned from an English corpus in Biology, onto a French
corpus of Curriculum Vitae, and vice versa, showing a good
robustness of the approaches compared to the state-of-the-art Support
Vector Machine (SVM).
Abstract: The study was a case study analysis about Thai Asia
Pacific Brewery Company. The purpose was to analyze the
company’s marketing objective, marketing strategy at company level,
and marketing mix before liquor liberalization in 2000. Methods used
in this study were qualitative and descriptive research approach
which demonstrated the following results of the study demonstrated
as follows: (1) Marketing objective was to increase market share of
Heineken and Amtel, (2) the company’s marketing strategies were
brand building strategy and distribution strategy. Additionally, the
company also conducted marketing mix strategy as follows. Product
strategy: The company added more beer brands namely Amstel and
Tiger to provide additional choice to consumers, product and
marketing research, and product development. Price strategy: the
company had taken the following into consideration: cost,
competitor, market, economic situation and tax. Promotion strategy:
the company conducted sales promotion and advertising. Distribution
strategy: the company extended channels its channels of distribution
into food shops, pubs and various entertainment places. This strategy
benefited interested persons and people who were engaged in the beer
business.
Abstract: This research presented in this paper is an on-going
project of an application of neural network and fuzzy models to
evaluate the sociological factors which affect the educational
performance of the students in Sri Lanka. One of its major goals is to
prepare the grounds to device a counseling tool which helps these
students for a better performance at their examinations, especially at
their G.C.E O/L (General Certificate of Education-Ordinary Level)
examination. Closely related sociological factors are collected as raw
data and the noise of these data are filtered through the fuzzy
interface and the supervised neural network is being utilized to
recognize the performance patterns against the chosen social factors.
Abstract: A spectrophotometric method was developed for simultaneous quantification of pseudoephedrine hydrochloride (PSE) triprolidine hydrochloride (TRI) using second derivative method (zero-crossing technique). The second derivative amplitudes of PSE and TRI were measured at 271 and 321 nm, respectively. The calibration curves were linear in the range of 200 to 1,000 g/ml for PSE and 10 to 50 g/ml for TRI. The method was validated for specificity, accuracy, precision, limit of detection and limit of quantitation. The proposed method was applied to the assaying and dissolution of PSE and TRI in commercial tablets without any chemical separation. The results were compared with those obtained by the official USP31 method and statistical tests showed that there is no significant between the methods at 95% confidence level. The proposed method is simple, rapid and suitable for the routine quality control application. KeywordsTriprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.
Abstract: Recent advances in wireless sensor networks have led
to many routing methods designed for energy-efficiency in wireless
sensor networks. Despite that many routing methods have been
proposed in USN, a single routing method cannot be energy-efficient
if the environment of the ubiquitous sensor network varies. We present
the controlling network access to various hosts and the services they
offer, rather than on securing them one by one with a network security
model. When ubiquitous sensor networks are deployed in hostile
environments, an adversary may compromise some sensor nodes and
use them to inject false sensing reports. False reports can lead to not
only false alarms but also the depletion of limited energy resource in
battery powered networks. The interleaved hop-by-hop authentication
scheme detects such false reports through interleaved authentication.
This paper presents a LMDD (Low energy method for data delivery)
algorithm that provides energy-efficiency by dynamically changing
protocols installed at the sensor nodes. The algorithm changes
protocols based on the output of the fuzzy logic which is the fitness
level of the protocols for the environment.
Abstract: The present paper was concerned primarily with the
analysis, simulation of the air flow and thermal patterns in a lecture
room. The paper is devoted to numerically investigate the influence
of location and number of ventilation and air conditioning supply and
extracts openings on air flow properties in a lecture room. The work
focuses on air flow patterns, thermal behaviour in lecture room where
large number of students. The effectiveness of an air flow system is
commonly assessed by the successful removal of sensible and latent
loads from occupants with additional of attaining air pollutant at a
prescribed level to attain the human thermal comfort conditions and
to improve the indoor air quality; this is the main target during the
present paper. The study is carried out using computational fluid
dynamics (CFD) simulation techniques as embedded in the
commercially available CFD code (FLUENT 6.2). The CFD
modelling techniques solved the continuity, momentum and energy
conservation equations in addition to standard k – ε model equations
for turbulence closure.
Throughout the investigations, numerical validation is carried out by
way of comparisons of numerical and experimental results. Good
agreement is found among both predictions.
Abstract: The utilize of renewable energy sources becomes
more crucial and fascinatingly, wider application of renewable
energy devices at domestic, commercial and industrial levels is not
only affect to stronger awareness but also significantly installed
capacities. Moreover, biomass principally is in form of woods and
converts to be energy for using by humans for a long time.
Gasification is a process of conversion of solid carbonaceous fuel
into combustible gas by partial combustion. Many gasified models
have various operating conditions because the parameters kept in
each model are differentiated. This study applied the experimental
data including three inputs variables including biomass consumption;
temperature at combustion zone and ash discharge rate and gas flow
rate as only one output variable. In this paper, response surface
methods were applied for identification of the gasified system
equation suitable for experimental data. The result showed that linear
model gave superlative results.
Abstract: The success of an e-learning system is highly
dependent on the quality of its educational content and how effective,
complete, and simple the design tool can be for teachers. Educational
modeling languages (EMLs) are proposed as design languages
intended to teachers for modeling diverse teaching-learning
experiences, independently of the pedagogical approach and in
different contexts. However, most existing EMLs are criticized for
being too abstract and too complex to be understood and manipulated
by teachers. In this paper, we present a visual EML that simplifies the
process of designing learning scenarios for teachers with no
programming background. Based on the conceptual framework of the
activity theory, our resulting visual EML focuses on using Domainspecific
modeling techniques to provide a pedagogical level of
abstraction in the design process.